reliable rfid communication and positioning system for …1045482/... · 2016. 11. 16. ·...

Reliable RFID Communication and Positioning Systemfor Industrial IoT

CHUANYING ZHAI

Doctoral Thesis in Information and Communication TechnologySchool of Information and Communication Technology

KTH Royal Institute of TechnologyStockholm, Sweden 2016

TRITA-ICT 2016:29ISBN 978-91-7729-165-7

KTH School of Information andCommunication Technology

SE-164 40 StockholmSWEDEN

Akademisk avhandling som med tillstånd av Kungl Tekniska högskolan framläggestill offentlig granskning för avläggande av teknologie doktorsexamen i Informations-och kommunikationsteknik måndagen den 12 december 2016 klockan 14.00 i Sal C,Electrum, Kungl Tekniska högskolan, Kistagången 16, Kista.

© Chuanying Zhai, October 2016

Tryck: Universitetsservice US AB

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Abstract

The Internet of Things (IoT) has the vision to interconnect everything ofthe physical world and the virtual world. Advanced automated and adaptiveconnectivity of objects, systems, and services is expected to be achieved underthe IoT context, especially in the industrial environment. Industry 4.0 withthe goal of intelligent and self-adaptable manufacturing is driven by the IoT.

The Object Layer, where real-time and reliable information acquisitionfrom the physical objects carried out, is the basic enabler in the 3-layer in-dustrial IoT system. Such acquisition system features deterministic access,reliable communication with failure resistance mechanism, latency-aware real-time response, deployable structure/protocol, and adaptive performance onvarious QoS demands.

This thesis proposes a reliable RFID communication system for acqui-sition in the industrial environment. A discrete gateway structure and acontention-free communication protocol are designed to fulfill the unique sys-tem requirements. Such gateway structure offers a flexible configuration ofreaders and RF technologies. It enables a full duplex communication be-tween the objects and the gateway. The designed MF-TDMA protocol canenhance the failure resistance and emergency report mechanism thanks tothe separation of control link and data link in the gateway. Specifically, anoptional ARQ mechanism, an independent/uniform synchronization and con-trol method, and a slot allocation optimization algorithm are designed besidestime-division and frequency-division multiplexing. Protocol implementationsfor different industrial situations illustrate the system ability for supportingthe demands of various QoS.

Finally, a 2.4-GHz/UWB hybrid positioning platform is explored basedon the introduced RFID system. Taking advantage of the UWB technology,the positioning platform can achieve positioning accuracy from meter level tocentimeter level. Hybrid tag prototype and specific communication processbased on the MF-TDMA protocol are designed. An SDR UWB reader net-work, capable of evaluating multiple algorithms, is built to realize accuratepositioning with an improved algorithm proposed.

Keywords: 2.4-GHz/UWB hybrid positioning, industrial IoT, MF-TDMA,QoS, reliable communication, RFID

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Sammanfattning

Sakernas Internet (IoT) har som vision att koppla samman allt i den fysis-ka världen med den virtuella världen. Avancerad automatiserad och adaptivanslutning av objekt, system och tjänster förväntas att uppnås inom ramenför Sakernas Internet. Särskilt i den industriella miljön. Det är således ocksåatt betraktas som en av de viktigaste drivkrafterna för den 4:e industriellarevolutionen, Industri 4.0, som har som målsättning att uppnå intelligent ochsjälvanpassningsbar tillverkning.

Arkitekturen i det industriella IoT-systemet består av tre delar: Objektsla-ger, Nätverkslager och Tjänstelager. Objektslagret, där förvärvande av till-förlitlig realtidsinformation från fysiska objekt utförs, är den grundläggan-de möjliggöraren. För dylik inhämtning från Objektlagret tillämpas lämp-ligast RFID-teknik, smart sensor-chipteknik, och kommunikationsprotokoll.Informationsinhämtningssystem för industriella tillämpningar kräver determi-nistisk access, tillförlitlig kommunikation med felmotståndsmekanism. Samtväntetidsmedveten prestanda för realtidssvar, möjlighet att applicera struk-tur/protokoll i flera områden, och flexibel möjlighet för QoS-krav beroendepå den specifika arbetsmiljön.

I denna avhandling har ett RFID-kommunikationssystem med hög tillför-litlighet föreslagits för informations-inhämtning i industriell miljö. En diskretGateway-struktur, där en samordnande enhet, en uppsättning avläsare, ochett konfliktfritt kommunikationsprotokoll är utformade för att uppfylla deunika systemkraven. En sådan Gateway-struktur möjliggör flexibel konfigu-ration av läsare och RF-tekniker med en koordinator. Det möjliggör också fullduplex-kommunikation mellan smarta objekt och gateway. Ett adaptivt pro-tokoll, ett utvecklat MF-TDMA-protokoll, för att förbättra fel motstånd ochrapportmekanism tillgodoses tack vare oberoende implementation av styrlänkoch datalänk i den diskreta Gateway-strukturen. Närmare bestämt; En valfriARQ-mekanism, en oberoende och enhetlig synkroniserings- och styrmetodoch en allokeringsoptimerande algoritm tillhandahålls förutom även schema-lagd tids- och frekvens-multiplexande kommunikationssätt. Implementationermed olika industriella förhållanden visar förmågan hos systemet för att mötakraven från olika QoS.

Slutligen utforskas en 2,4-GHz RF- och UWB- hybridpositioneringsplatt-form baserat på den introducerade RFID-systemet. Genom att dra full nyt-ta av den fina upplösningen i tidsdomän för UWB-tekniken, kan positione-ringsplattformen uppnå positioneringsnoggrannhet från meternivå (med 2,4GHz RF) till centimeternivå (med UWB). En specifik kommunikationspro-cess byggd på MF-TDMA och en prototyp av en hybrid-tagg utvecklades.Ett SDR-UWB-läsarnätverk som kan använda flera algoritmer, har byggtsför plattformen för att uppnå exakt positionering med en förbättrad positio-neringsalgoritm.

Keywords: 2,4-GHz RF- och UWB- hybridpositionerings, industriell IoT,MF-TDMA, QoS, tillförlitlig kommunikation, RFID

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Acknowledgments

First, I would like to express my sincere gratitude and respect to my supervisorsProf. Hannu Tenhunen, Dr. Zhuo Zou and Prof. Lirong Zheng for the continuoussupport of my Ph.D study and research. I am grateful to Hannu for his patientguidance in all the time of research and writing of this thesis. I sincerely appreciateto Zhuo, my co-supervisor, without his help, I could not imagine when I can getmy first journal paper published. Each progress I have made during the long PhDstudy, cannot be separated from his encouragement and assistance. My specialthanks to Prof. Zheng for providing me the opportunity to join the iPack group.He can always bring creative ideas each time I have discussed with him. I appreciatehaving such good supervisors and mentors for my Ph.D life.

Besides, I would like to thank Prof. Zhonghai Lu. He helped me a lot at thebeginning of my PhD study. And many thanks to Dr. Qiang Chen. Dr. Chenhas shared a lot of useful and interesting things in both the daily life and researchexperience in Sweden. Without his help, I cannot get me Swedish summary of thisthesis ready.

I am very grateful to the former and current members of my group for theircontinuous and selfless supports. Jia Mao, for his unique insights of UWB trans-mitter and receiver. The discussions with him have brought me some advice for theimplementation of UWB based positioning platform from the circuit aspect. Dr.Majid Baghaei, for his prototype design UWB transmitter. Wei Ouyang, for hisadvice in embedded system programming. And thanks to Dr. Jue Shen, Qin Zhou,Dr. Ning Ma, Dr. Geng Yang, Dr. Zhi Zhang, Dr. Li Xie, Jie Gao, Qiansu Wan,Dr. Yi Feng, Dr. Liang Rong for accompanying me and supporting me along theresearch journey. Special thanks to Pei Liu and Qin, for their help of accommoda-tion. Thanks to the new PhD colleagues Kunlong Yang, and Yuxiang Huan. And Ireally appreciate all my friends, especially to those not mentioned, both in Swedenand in China, thank you indeed for helping me.

I sincerely appreciate my colleague Amleset Kelati and Mohammad Badawi.They gave me some advice and helped me a lot during the application processof my thesis defense. Then I would like to present my gratitude to the advancedreviewer, the committee members, my opponent and the chairman for coming toattend and assist my disputation.

I would also express my appreciation to all the colleagues from the PhD of-fice and Alina Munteanu for assisting the administrative work and the applicationprocess.

At the end, I would like to thank my family, without your support and un-derstanding, I cannot have this valuable and memorable time in Sweden. Specialthanks to my husband, for his accompany.

Chuanying Zhai,Autumn 2016, Stockholm

Contents

Contents vii

List of Figures ix

List of Tables xii

List of Acronyms xiii

List of Publications xv

1 Introduction 11.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 The Internet of Things . . . . . . . . . . . . . . . . . . . . . . 11.1.2 Enabling Technologies . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.2.1 The Fourth Generation of Industry . . . . . . . . . . . . . . . 31.2.2 Challenges of System Implementation for the Industrial IoT . 41.2.3 Imperious Demand on Ubiquitous Positioning . . . . . . . . . 6

1.3 Contributions and Thesis Organization . . . . . . . . . . . . . . . . . 7

2 Industrial IoT and RFID System 112.1 Architecture of the Industrial IoT . . . . . . . . . . . . . . . . . . . . 11

2.1.1 IoT System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.1.2 Characteristics of the Acquisition System . . . . . . . . . . . 13

2.2 Industrial IoT System . . . . . . . . . . . . . . . . . . . . . . . . . . 142.2.1 Acquisition System Topology . . . . . . . . . . . . . . . . . . 142.2.2 System Topology for Industrial IoT . . . . . . . . . . . . . . . 16

2.3 RFID System for Industrial IoT . . . . . . . . . . . . . . . . . . . . . 182.3.1 RFID Components . . . . . . . . . . . . . . . . . . . . . . . . 182.3.2 Active RFID Technologies . . . . . . . . . . . . . . . . . . . . 19

2.4 Protocols and Standards . . . . . . . . . . . . . . . . . . . . . . . . . 222.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

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viii CONTENTS

3 Reliable RFID Communication System with QoS Capability 253.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253.2 Proposed System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.2.1 System Architecture . . . . . . . . . . . . . . . . . . . . . . . 253.2.2 MAC Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . 273.2.3 Synchronization . . . . . . . . . . . . . . . . . . . . . . . . . 283.2.4 Optional ARQ . . . . . . . . . . . . . . . . . . . . . . . . . . 283.2.5 Packet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.2.6 Slot Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . 313.2.7 Communication process . . . . . . . . . . . . . . . . . . . . . 313.2.8 Protocol Implementation . . . . . . . . . . . . . . . . . . . . 34

3.3 QoS Protocol Implementation . . . . . . . . . . . . . . . . . . . . . . 353.3.1 MF-TDMA for Energy-constraint Monitoring . . . . . . . . . 353.3.2 MF-TDMA for Latency-constraint Tracking . . . . . . . . . . 363.3.3 MF-TDMA for Reliability-aware Control . . . . . . . . . . . 413.3.4 Throughput and Packet Delivery Ratio . . . . . . . . . . . . 44

3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

4 2.4-GHz/UWB Hybrid Positioning Platform 494.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.1.1 Context Awareness of the Industrial IoT . . . . . . . . . . . . 494.1.2 Indoor Positioning Techniques . . . . . . . . . . . . . . . . . 494.1.3 Accurate Positioning using the UWB Technology . . . . . . . 51

4.2 2.4-GHz/UWB Positioning Platform . . . . . . . . . . . . . . . . . . 524.2.1 System Architecture . . . . . . . . . . . . . . . . . . . . . . . 544.2.2 Hybrid tag . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554.2.3 Communication Process . . . . . . . . . . . . . . . . . . . . . 554.2.4 State-of-the-art UWB Receiver . . . . . . . . . . . . . . . . . 584.2.5 The Proposed SDR UWB Receiver . . . . . . . . . . . . . . . 604.2.6 Implementation and Experiment . . . . . . . . . . . . . . . . 62

4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

5 Conclusions and Future Work 675.1 Thesis Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Bibliography 71

List of Figures

1.1 A overlook of the IoT in industries [26]. . . . . . . . . . . . . . . . . . . 21.2 Development of industry: from the first generation to the fourth gener-

ation [48]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3 Development roadmap of the IoT [59]. . . . . . . . . . . . . . . . . . . . 6

2.1 The basic IoT system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2 The Industrial IoT structure. . . . . . . . . . . . . . . . . . . . . . . . . 122.3 Basic system topologies. . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.4 System topology for the industrial IoT. . . . . . . . . . . . . . . . . . . 172.5 The operating frequency of the IEEE 802.15.4 compliant technologies [78]. 192.6 Pulses and spectrum of the UWB signal compared with the conventional

sinusoidal narrow-band signal. . . . . . . . . . . . . . . . . . . . . . . . . 202.7 The coexistence of the UWB and other technologies. . . . . . . . . . . . 212.8 Development of the RFID towards the industrial IoT and Industry 4.0. 21

3.1 The proposed system architecture. Adapted from Paper I . . . . . . . . 263.2 The topology of the proposed system. . . . . . . . . . . . . . . . . . . . 273.3 An overview of the proposed MF-TDMA protocol. Adapted from Paper

II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283.4 The ARQ method: ARQ for the tags allocated to the same transmission

channel. Adapted from Paper I . . . . . . . . . . . . . . . . . . . . . . . 293.5 The packet format.Adapted from Paper I . . . . . . . . . . . . . . . . . 293.6 The flowchart of a tag in the communication process. Adapted from

Paper I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323.7 The flowchart of the coordinator in the communication process. Adapted

from Paper I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333.8 Four-phase communication process of the MF-TDMA protocol.Adapted

from Paper III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343.9 Protocol description for the energy-constraint monitoring application.

Adapted from Paper III . . . . . . . . . . . . . . . . . . . . . . . . . . . 353.10 Optimization of the guard time and transmission time in each slot for

reducing the synchronization rate. . . . . . . . . . . . . . . . . . . . . . 36

ix

x List of Figures

3.11 Protocol description for the latency-constraint tracking application. Adaptedfrom Paper III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

3.12 Estimation of energy consumption of both energy-constraint and latency-constraint scenarios. Packet length: 60 bytes, reduced packet: 40 bytes,update cycle: 10 minutes, current for transmission, reception and sleep:30 mA, 15 mA, and 1 µA, synchronization interval: 37.5 minutes and28 seconds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

3.13 Optimization of the slot allocation for reducing queuing time for trans-mission. Adapted from Paper I . . . . . . . . . . . . . . . . . . . . . . . 39

3.14 Queuing time for 50 ms (λ = 1/(50ms)) expectation of generation inter-val of 1000 tags using np-CSMA protocol, the initial MF-TDMA proto-col, and the slot optimized MF-TDMA protocol. Adapted from PaperI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

3.15 Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using np-CSMA protocol, the initial MF-TDMAprotocol, and the slot optimized MF-TDMA protocol. Adapted fromPaper I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.16 Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using 5 channels. Adapted from Paper I . . . . . . 42

3.17 Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using 6 channels. Adapted from Paper I . . . . . . 42

3.18 Protocol description for the reliability-aware control application. Adaptedfrom Paper III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.19 The PDR and the throughput curves for different tag allocations. . . . . 45

4.1 Comparison of power, coverage, and data rate of tags implemented bydifferent short range wireless technologies. . . . . . . . . . . . . . . . . . 52

4.2 Hardware and software structure of the proposed positioning platform. . 534.3 The hybrid technology based positioning system. . . . . . . . . . . . . . 544.4 The UWB/2.4-GHz hybrid tag. . . . . . . . . . . . . . . . . . . . . . . . 554.5 The communication process used in each cluster. . . . . . . . . . . . . . 564.6 The state transition of the RF module of each hybrid tag. . . . . . . . . 564.7 The operation flowchart of the 2.4-GHz/UWB hybrid positioning. Adapted

from Paper IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574.8 Architecture of the correlator-based (Matched filter) UWB receiver. . . 594.9 Architecture of the energy detection (ED) based UWB receiver. . . . . . 594.10 Architecture of the self-delay based (AcR) UWB receiver. . . . . . . . . 594.11 The block diagram of the proposed SDR-based ToA estimator. . . . . . 604.12 The ToA estimation process using the proposed ToA estimator. . . . . . 614.13 The structure of the SDR UWB reader network. . . . . . . . . . . . . . 624.14 The overview of the platform implementation. . . . . . . . . . . . . . . . 634.15 The absolute ToA estimation based on the received UWB signal. . . . . 634.16 A positioning example using TDoA estimation. . . . . . . . . . . . . . . 64

List of Figures xi

4.17 The RMSE distribution of the estimated locations of one test point over1600 times estimations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

4.18 Estimated average power consumption of Tx and Rx of each tag (2.4-GHz: 32 mA for Tx and 27 mA for Rx, the Tx period for positionupdate is 5 ms, the Rx period for command is 5 ms, and Rx period forsynchronization is 1 ms; UWB: 16 mA for Tx, the Tx period for positionupdate is 1 ms). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

List of Tables

2.1 The standards proposed for supporting the IoT. . . . . . . . . . . . . . 22

3.1 The MAC control word. Adapted from Paper I . . . . . . . . . . . . . . 30

4.1 RTLS solutions. Adapted from Paper IV . . . . . . . . . . . . . . . . . . 50

xii

List of Acronyms

xiii

xiv LIST OF ACRONYMS

AcR AutoCorRelationADC Analog-to-Digital ConverterAoA Angle of ArrivalARQ Automatic Repeat QueryASIC Application-Specific Integrated CircuitCoO Cell of OriginCSMA Carrier Sense Multiple AccessDR Dead ReckoningED Energy DetectorETSI European Telecommunications Standards InstituteFDMA Frequency Division Multiple AccessFP FingerPrintingGPS Global Positioning SystemH2C Human-to-ComputerHF High FrequencyIC Integrated CircuitIETF Internet Engineering Task ForceIoT Internet of TingsIR-UWB Impulse Radio UWBISM Industrial, Scientific and MedicalKF Kalman FilterLF Low FrequencyLLS Linear Least SquareM2M Machine-to-MachineMAC Media Access ControlMEMS Micro-ElectroMechanical Systemsms millisecondsNFC Near Field Communicationns nanosecondsPDR Packet Delivery RatioPLR Packet Loss Rateps picosecondsPSD Power Spectral DensityQoS Quality of ServiceRFID Radio Frequency IDentificationRMSE Root Mean Square ErrorRSS Received Signal StrengthRTLS Real-Time Locating SystemsRToF Round-Trip of FlightSDR Software Defined RadioSFD Start Frame DelimiterTDMA Time Division Multiple AccessTDoA Time Difference of ArrivalToA Time of ArrivalUHF Ultra-High FrequencyUWB Ultra-Wide BandwidthWSN Wireless Sensor Network

List of Publications

Papers included in the thesis:

1. Chuanying Zhai, Zhuo Zou, Qiang Chen, Lida Xu, Li-Rong Zheng, and HannuTenhunen. "Delay-Aware and Reliability-Aware Contention-Free MF-TDMAProtocol for Automated RFID Monitoring in Industrial IoT," in Journal ofIndustrial Information Integration, vol.3, 2016, pp. 8-19.

2. Chuanying Zhai, Zhuo Zou, Qiang Chen, Lirong Zheng, and Hannu Ten-hunen. "High-Throughput and High-Efficiency Multiple Access Scheme forIEEE802.15.4 based RFID Sensing," 2015 IEEE International Conference onUbiquitous Wireless Broadband (ICUWB), Montreal, QC, 2015, pp. 1-5.

3. Chuanying Zhai, Zhuo Zou, Yifan Qin, Ning Ma, Yuxiang Huan, Qiang Chen,Lirong Zheng, and Hannu Tenhunen. "QoS based RFID System for SmartAssembly Workshop," RFID Technology and Applications (RFID-TA), 2016IEEE International Conference on, Shunde, China, 2016.

4. Chuanying Zhai, Zhuo Zou, Qin Zhou, Jia Mao, Qiang Chen, Hannu Ten-hunen, Lirong Zheng, and Lida Xu. "A 2.4-GHz ISM RF and UWB Hy-brid RFID Real-Time Locating System for Industrial Enterprise Internet ofThings," in Enterprise Information Systems (Taylor & Francis Group), Avail-able online March 2016, pp. 1-18.

5. Chuanying Zhai, Zhuo Zou, and Lirong Zheng. "Software Defined Radio IR-UWB Positioning Platform for RFID and WSN Application," 2012 IEEEInternational Conference on Ultra-Wideband (ICUWB), Syracuse, NY, 2012,pp. 501-505.

Papers not included in the thesis:

6. Chuanying Zhai, Zhuo Zou, Qiang Chen, Lirong Zheng, and Hannu Tenhunen."Optimization on Guard Time and Synchronization Cycle for TDMA-basedDeterministic RFID System," RFID Technology and Applications (RFID-TA),2015 IEEE International Conference on, Tokyo, 2015, pp. 71-75.

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xvi LIST OF PUBLICATIONS

7. Chuanying Zhai, Zhuo Zou, and Lirong Zheng. "A Software Defined Ra-dio Platform for Passive UWB-RFID Localization," Wireless InformationTechnology and Systems (ICWITS), 2012 IEEE International Conference on,Maui, HI, 2012, pp. 1-4.

8. Zhuo Zou, Botao Shao, Qin Zhou, Chuanying Zhai, Jia Mao, Majid Baghaei-Nejad, Qiang Chen, and Lirong Zheng. "Design and Demonstration of PassiveUWB RFIDs: Chipless versus Chip Solutions," RFID-Technologies and Ap-plications (RFID-TA), 2012 IEEE International Conference on, Nice, 2012,pp. 6-11.

9. Dongxuan Bao, Zhuo Zou, Yuxiang Huan, Chuanying Zhai, Hannu Tenhunen,and Lirong Zheng. "A Smart Catheter System for Minimally Invasive BrainMonitoring." in Proceedings of the International Conference on BiomedicalElectronics and Devices, SciTePress, 2015, pp. 198-203.Patent:

10. Chuanying Zhai, Zhuo Zou, Qiang Chen, Lirong Zheng, and Hannu Tenhunen."A Multi-Antenna Ultra-wide Bandwidth (UWB) Receiver," US ProvisionalPatent, 2015.

Chapter 1

Introduction

1.1 Background

1.1.1 The Internet of Things

The concept of the Internet of Things(IoT) was proposed by MIT Auto-ID Lab in1999 [1] and formally introduced by the ITU Internet Report in 2005 [2]. From2010, the IoT which has the vision to interconnect everything of both the physicalworld and the virtual world has attracted large amount of attention [3]. Beyondthe conventional human-to-computer (H2C)/machine-to-machine (M2M) commu-nications, advanced connectivity of services, systems, and objects while covering avariety of protocols, domains, and applications [4, 5] is expected to be presentedby the introduction of the IoT. It is predicted that by 2025 more than 50 billionobjects can be reached through the connection of the IoT [6, 7].

In the IoT, the "thing" can be a person with wearable sensor for remote heartmonitoring, a herd attached to a bio-chip identifier for identification and positiontracking, a machine cooperated with other tools and raw materials with micro-controller for manufacturing, or a computer with authorization for power manage-ment of city electricity. Evolved from wireless technologies, network technologies,micro-electromechanical systems (MEMS), and service, the IoT thus provides animmediate access to information of all the things, both natural and man-made,and motivates high efficiency and productivity in both business and daily life [8].Especially, under the context of the industrial environment, the IoT technologyhas introduced a wide range of business opportunities and economic applications invarious practical applications including utility grid [9–11], transportations [12, 13],healthcare [14–16], industrial automation [17, 18], manufacturing and assembly[17, 19–21], livestock and agriculture [22–25]. Figure 1.1 is application instances ofthe IoT from the enterprise aspect of view [26].

1

2 CHAPTER 1. INTRODUCTION

Figure 1.1: A overlook of the IoT in industries [26].

1.1.2 Enabling TechnologiesFrom the technology aspect, the IoT is enabled by the improvements of the under-lying technologies in terms of sensor and microprocessor designs, Radio FrequencyIdentification (RFID) and communication technologies, and advanced connectivi-ties and networks [27, 28].

Smart Sensors

As the development of the technology of chip electronics, the size and cost of thechip decline and the performance improves. It is feasible to produce wearable andinjectable small high-speed sensors even on the flexible substrates. Additionally, therises of microprocessors and multi-core processors [29, 30] capacitate huge increas-ing on performance and efficiency of the sensors. The sensors that can conditionthe sensed data, program custom-built functions for collecting valuable informa-tion, and communicate with others over wire or wireless medias become intelligent,that is, the smart sensors [31]. The smart sensors make their attached objectsclosely linked to the IoT via the capabilities of sensing, digital processing and radiocommunicating [32].

Communication and Network Protocols

To connect the tremendous physical objects to the Internet, advanced protocol, onone hand, such as IPv6 [33, 34] was introduced to accommodate the requirementsof addressing all the objects. On the other hand, the efficient and reliable networksare needed to promise the communications of the objects with others and computersystems.

Besides, various communication technologies and the corresponding protocolssuch as Wi-Fi, Bluetooth, Bluetooth Low Energy, ZigBee, IEEE 802.15.4, Z-Wave,

1.2. MOTIVATION 3

LTE, Near Field Communication (NFC), RFID, Ultra-Wide Bandwidth (UWB),and IrDA, can be used in the IoT [35–39].

RFID Technology

In addition to sensing, identification, which is crucial to name and match servicesin the IoT, is another key enabler. Since there are billions of objects connected inthe IoT, apart from their addresses for network, unique identification is demandedfor correctly collecting information from the object.

The RFID technique, which can automatically identify via radio waves the tagsattached to the objects, is considered as the prerequisite of the IoT. Compared withconventional barcode, the RFID enables faster identification rate, longer operationrange, larger data capability, reuse and read-write feasibility, and higher level ofsecurity by storing the identification information of the objects in the RFID tags.

1.2 Motivation

1.2.1 The Fourth Generation of Industry

Increasing competitions and global challenges of customer requirements and volatilemarket developments force more industrial companies to turn to high-tech method-ologies. The industries are therefore transforming to a new era of evolution which isknown as Industry 4.0, as shown in Figure 1.2 [40]. This development is driven byseveral factors. First is the M2M technology which enables large-scale automatedproduction by introducing self-learn and self-organize machines to the workshops[41, 42]. The second driver is the development of high-speed broadband technology[43, 44]. It makes the real-time data exchanging achievable anytime anywhere. Thethird driver is the cloud computing and big data. Thanks to the rapid advance ofsuch cloud computing and big data technologies, massive data storage, analysis,and processing become feasible in the industry. The last driver is the IoT, whichcan connect everything into a huge network. Through the industrial IoT, togetherwith the help of sensors, data acquisition solutions, and network technologies, theindustries can possess not only intelligent, and self-adaptable machines/productsbut also self-organized system and manufacturing [45].

In summary, the fourth generation of industry expects worry-free system withthe abilities in terms of self-configuration, self-diagnostics, self-maintenance, andself-optimization [46, 47]. Such system also enables a better visibility into themanufacturing. The resource consumption, equipment performance, and the safetystate in the industry can be explicitly observed. This can thus enhance the industryefficiency. It is notable that the industry is gradually experiencing the IoT phase,that is, the industrial IoT.


First (Industry 1.0)Industrial revolution

Introduction of mechanical production facilities

Introduction of a division of labor and mass production

Second (Industry 2.0)Industrial revolution

Third (Industry 3.0)Industrial revolution

Automate production

First mechanical loom,1784.

First assembly line Cincinnati slaughterhouses, 1870.

First programmable logic control (PLC), Modicon084, 1969.

electric and IT systems

Fourth (Industry 4.0)Industrial revolution

Cyber-physical systems

electrical energywater and steam power

Figure 1.2: Development of industry: from the first generation to the fourth gen-eration [48].

1.2.2 Challenges of System Implementation for the IndustrialIoT

• ScalabilityThe ability of scalable and deployable of an IoT system is highly desired forsupporting the industrial environment [49] because of the huge number ofobjects connected and distributed at indoor, outdoor, or multiple floors. Forexample, in a manufacturing workshop, from raw materials, tools, assemblyline, products, machines and facilities, to other monitoring equipment are allconnected. Along with the production process, some of the components maybe moved from one place to another, and some of them may be assembledand packaged. The system should be able keep tracking of the components topromise continuous control. In addition, the system should have the abilityto support the change of the states of each object. That is, when an objectis used up, or it is assembled together to others, the system has to adjust thecontrol of the object or release the space for the newly involved object.

• FlexibilityThe flexibility of the industrial IoT system represents its adaptive abilityfor supporting multiple hardware/protocol infrastructures, the compatibilityof providing seamless service for the objects from other systems, and theuniformity for multiple functions in one system.First, there have been a lot of communication systems proposed for collectinginformation from the objects and interacting for the IoT [50–53]. However,most of the systems and protocols are designed based on a single microproces-sor and wireless interface to support only one communication technology andone compliant protocol. As the universal development of the IoT, the smarttag which can comprise multiple processors and support multiple wireless in-

1.2. MOTIVATION 5

terfaces [49, 54] is expected for handling complex computing and communica-tion requirements. Consequently, it requests the system and it correspondingprotocol to be feasible to sustain such multi-core multi-interface even multi-protocol hardware infrastructure.

When shifting the existing network infrastructures to the IoT, the compati-bility is another challenge for the system implementation. Because the lackof universal protocols/standards, the designed systems and some of the ma-chines are using various technologies and protocols for communication. An-other challenge is that in some of the industrial environments, only specificwireless technologies are applicable. For instance, in a metal fabrication work-shop, most of the wireless techniques such UWB, Bluetooth, and ZigBee, canhardly be used. Additionally, in the same industrial environment, there existvarious contexts of usage. For example, in a fruit warehouse, there are sen-sors for monitoring to indicate the state change, and smart tags attached tothe packages of fruit for identifying the time and transportation information.The two types of tag feature different information format and various commu-nication characteristic. Consequently, it is desired that the system designedfor the industrial IoT should be able to provide equivalent performance whendifferent technologies or multiple communication protocols are employed.

• Time/Energy Efficiency

From the market aspect, one of the significant trends of the industrial IoTis to provide greater customer focus and more customer-specific service [55].The main goal of introducing the IoT to the industry is to achieve shorter leadtimes by optimizing the process time and reducing the response time of faultsto boost the efficiency of industries. From the industrial aspect, it is expectedto minimize the energy consumption while maximizing the system throughputand quality by applying the smart machines and the smart networked system[56]. Therefore, as the cornerstone of the implementation of industrial IoT,the data collection system which takes care of the data sensing and interactingbased on the physical objects is liable for providing more latency-efficient andenergy-efficient service.

• Cost

Cost is what the industries concern most when turning into the industrialIoT. Although most of the technologies employed such as robotics, biotech-nology, sensor technology, and microelectronics technology, are introduceddecades ago. It is the reduction in the cost of computing power and mi-croelectronics process enables the technologies to be used in the industrialenvironment [57, 58]. Consequently, realizing the system in a non-complexand easy-maintenance manner is the goal of the industrial IoT application.


1.2.3 Imperious Demand on Ubiquitous Positioning

Figure 1.3 illustrates a roadmap of the development of the IoT [59]. It can be seenthat accurate positioning capability is an indispensable factor as the growth of theIoT. Under the context of the industrial IoT, the objective of ubiquitous positioningis to locate people, products, machines, and other objects anytime anywhere bothin the indoor and the outdoor condition [60].

RFID tags for facilitating routing inventorying and loss prevention

Surveillance, security, healthcare, transport, food safety, document management

Locating people and the entire objects both in business and daily life

Teleoperation and telepresence. Ability to monitor and control distant objects

Demand for expedited logistics

Cost reduction, universal application

Indoor and outdoor location ability of devices and persons to receive geolocation signals

Miniaturization, power-efficient electronics, multi-core, broadband, cloud computing

Advance sensor fusions, services oriented software agents

Tech

nolo

gy R

esea

rch

Time2000 2010 2020

Supply- Chain Helpers

Vertical-Market Applications

Ubiquitous Positioning

Cyber-physical world

Figure 1.3: Development roadmap of the IoT [59].

Especially, for the context-aware industrial IoT, the capability of accurate po-sitioning is essential. For example, with the help of the smart sensors and wirelesscommunication, the production process can be automated controlled. However,when mechanical fault or run-time error occurs, it demands the system/network becapable of accurately locating the position of fault/error both in the physical spaceand in the cyber world [61, 62]. Another practical need appears in the safeguard ofvaluable objects including people in special working environments. It is demandedin the fields like fresh fruits/assets transportation [63, 64], tracking of worker inmining, fire fighting and other dangerous conditions, and so on [65–67]. Moreover,the ubiquitous positioning systems applied in factories, farms, and utilities enablesimprovement of productivity and value by providing real-time location informationof products, animals, and facilities. The stored location data also offers valuableinformation for optimizing progress management, resource allocation, and breedingmethod [68].

From another perspective, to realize the ubiquitous positioning in the industrialIoT, it requires the system to execute both the communicating and the locating.

1.3. CONTRIBUTIONS AND THESIS ORGANIZATION 7

Up to now, there is no international approach for developing such ubiquitous posi-tioning system and its associated infrastructure. That is, the existing positioningsystems can hardly offer a satisfied performance in the industrial environment. Forinstance, the Global Positioning System (GPS) can not provide accurate locationinformation for indoors. The systems designed for using in the indoor environment,such as the radio based WiFi positioning [69] and the non-radio based magneticpositioning [70], are limited either by the expense of the equipment/installation orthe accuracy. Moreover, as the working scenarios of the industries contain bothindoor and outdoor condition, it requires the positioning system to be capable ofsupporting seamless positioning and precision. Meanwhile, the various accuracydemands in different applied conditions rely on a number of numerical comput-ing or a group of fitting comparison. This requires the system to have not only astrong computing capability for processing the location data but also an adaptivealgorithm for supporting flexible accuracy in complex environments [71].

1.3 Contributions and Thesis Organization

The thesis is organized as follows:

Chapter 2

In Chapter 2, the architecture of the IoT system is first introduced. Based onthe architecture, an acquisition system which takes care of the communicationamong the physical objects and the network server is pointed for the industrial IoTarchitecture. Then the appreciated architecture, the communication techniques andthe corresponding protocols design of the acquisition system are discussed.

Chapter 3

Based on the characteristics of the acquisition system, an RFID communicationsystem with the discrete structure gateway and contention-free protocol is designedin this chapter. The detailed implementations of the RFID system and the protocolsfor resolving the requirements, that is deterministic access, deployable capability,flexible latency, reliable communication, and QoS performance, of the industrialapplications are illustrated. Additionally, under the consideration of various QoSdemands, instance implementations of the designed RFID communication systemare demonstrated to explain the flexibility of the designed system.

Contributions:

• First, a discrete-structure gateway based RFID system is designed. The de-signed system architecture enables multi-channel multi-technique communi-cations and flexible system capacity by adjusting the occupied number ofchannels or the number/type of readers. As it separates the conventional


function of a gateway device to a coordinator and a set of readers, a dedicatedfrequency channel can be used in the coordinator to perform all the controlwork, meanwhile, the readers can focus on reception. Second, a delay-awareand reliability-aware communication protocol is designed. To guarantee theperformance in various industrial applications, the designed communicationprotocol, which is called MF-TDMA protocol, uses an optional ARQ mecha-nism, the independent/uniform synchronization and control manner, and theslot allocation optimization method to lower the delay, improve the reliability,and support the capability of adaptive quality. Third, QoS based protocolimplementations are explores. To illustrate how the system and its protocolcan be used for different qualities of performance, the communication processis expressed as a 4-stage process. Based on this, instance implementationsfor different performance requests are designed as reference for the industrialapplications.

The included papers:

• Paper I: Chuanying Zhai, Zhuo Zou, Qiang Chen, Lida Xu, Li-Rong Zheng,and Hannu Tenhunen. "Delay-Aware and Reliability-Aware Contention-FreeMF-TDMA Protocol for Automated RFID Monitoring in Industrial IoT," inJournal of Industrial Information Integration, vol.3, 2016, pp. 8-19.

• Paper II: Chuanying Zhai, Zhuo Zou, Qiang Chen, Lirong Zheng, and HannuTenhunen. "High-Throughput and High-Efficiency Multiple Access Schemefor IEEE802.15.4 based RFID Sensing," 2015 IEEE International Conferenceon Ubiquitous Wireless Broadband (ICUWB), Montreal, QC, 2015, pp. 1-5.

• Paper III: Chuanying Zhai, Zhuo Zou, Yifan Qin, Ning Ma, Yuxiang Huan,Qiang Chen, Lirong Zheng, and Hannu Tenhunen. "QoS based RFID Systemfor Smart Assembly Workshop," RFID Technology and Applications (RFID-TA), 2016 IEEE International Conference on, Shunde, China, 2016.

Chapter 4

A positioning platform which hybrids the 2.4-GHz RF and the UWB techniques forproviding accuracy from meter level to centimeter level is explored in this chapter.The RFID tag for positioning application is designed to have both the 2.4-GHz RFand the UWB interface for updating the object’s location on demands. To takeadvantage of the UWB technique in the time domain, time of arrival (ToA) andtime difference of arrival (TDoA) based positioning algorithms are proposed. Anda software defined radio (SDR) UWB reader as part of the platform is introducedfor demonstrating the positioning.

Contributions:

1.3. CONTRIBUTIONS AND THESIS ORGANIZATION 9

• First, a positioning platform based on hybrid communication technologies isdesigned. It uses a 2.4-GHz transceiver with 8051 core as the coordinator tosend controls to the tags. And both the 2.4-GHz RF and the UWB readersare used as the readers to receive the tags’ information. Second, a hybridtag which contains the same 2.4-GHz transceiver and a UWB transmitter isdesigned. It enables the tag to receive the command from the coordinatorthrough the 2.4-GHz receiver, and to transmit data to the readers througheither the 2.4-GHz transmitter or the UWB transmitter. Without the UWBreceiver, the hybrid tag can work in a power-effective manner while supportingthe capability of centimeter level accuracy thanks to the pulse-based UWBsignals. Third, an improved positioning algorithm is proposed to provide highconfidence of accurate positioning performance. Fourth, an SDR UWB readernetwork is built based on an oscilloscope. Since it supports the third partyprogram, multiple ToA/TDoA based positioning algorithms are achievable.The implementation of this hybrid positioning platform is considered as aninstance demonstration of the designed RFID system.

The included papers:

• Paper IV: Chuanying Zhai, Zhuo Zou, Qin Zhou, Jia Mao, Qiang Chen, HannuTenhunen, Lirong Zheng, and Lida Xu. "A 2.4-GHz ISM RF and UWBHybrid RFID Real-Time Locating System for Industrial Enterprise Internetof Things," in Enterprise Information Systems (Taylor & Francis Group),Available online March 2016, pp. 1-18.

• Paper V: Chuanying Zhai, Zhuo Zou, and Lirong Zheng. "Software DefinedRadio IR-UWB Positioning Platform for RFID and WSN Application," 2012IEEE International Conference on Ultra-Wideband (ICUWB), Syracuse, NY,2012, pp. 501-505.

Chapter 5

This chapter concludes the thesis and discusses the future work under the consid-erations of the ubiquitous industrial applications towards the IoT.

Chapter 2

Industrial IoT and RFID System

2.1 Architecture of the Industrial IoT

2.1.1 IoT System

From the view of application types, the IoT system can be basically modeled bya three-layer architecture [72] consisting of the Object Layer, the Network Layer,and the Application Layer as shown in Figure 2.1.

The Objects Layer includes the ’things’ which are connected to the Internet. In

Application Layer

Network Layer

Object Layer

Figure 2.1: The basic IoT system.

11

12 CHAPTER 2. INDUSTRIAL IOT AND RFID SYSTEM

ServiceApplication

Network Layer

Gateway

Objects

Sensors (Temp., Accel., Power, Light, etc.)/Embedded chips

RFID Techniques (ZigBee, Bluetooth, UWB, 6LowPAN, etc.)

Network (WiFi, Fiber, Mobile, etc.)

Object Layer

Figure 2.2: The Industrial IoT structure.

this layer, information of the objects is acquired, digitized and then transferred tothe Network Layer. It relies on various sensors and embedded chips to achieve stateinformation such as temperature, speed, pressure, etc., and inherent informationsuch as identification, ingredient, usage, etc., respectively.

The function of the Network Layer can be divided into three parts: the ab-straction, the service management, and the middleware. The abstraction refers tothe wireless interface which is used to transport the data from the Object Layerto the service management. Then the data is processed and digested by the servermanagement according to different application requirements. However, there mayexist different types of service over the IoT implementations, the objects can onlyconnect and communicate to others using the same service. Thus, before the in-formation is delivered to the Application Layer, a middleware which is employedto perform ubiquitous computations and decisions based on different applicationrequests.

As shown in the basic IoT system structure, sensors or embedded chips aresupposed to communication directly with the central server. This structure may notfit most of the IoT application well especially in the industrial environment becauseof the huge amount of objects and the various types of information. Therefore, asillustrated in Figure 2.2, the gateway device is used at the Object Layer for theindustrial IoT system [73]. Instead of a direct connection between the objects andthe server/Internet, the objects communicate via the gateway. In the practicalimplementations, there are multiple gateway devices and each device can handlethe work of data collection, data exchange, processing, and communication formultiple objects. This guarantees the efficient and accurate management of the

2.1. ARCHITECTURE OF THE INDUSTRIAL IOT 13

huge volume of data in the industrial IoT system. The gateway has both theinterface for communicating with the objects and the interface for connecting tothe upper network. Hence, one gateway should be able to take care of multipletechnologies/standards and objects. The system applied in the Object Layer, thatis an acquisition system, is then comprised of the gateway devices and the objects(attached to sensors and embedded chips) as the basis of the industrial IoT system.

2.1.2 Characteristics of the Acquisition SystemConsidered the industrial environments and its requirements, the acquisition systemshould feature a number of unique characteristics as illustrated in the followingparts.

• DeterminacyUnlike the IoT system for consumer applications which need to handle a largenumber of random scenarios, the industrial applications are normally deter-ministic. That is, first the objects connected to the network such as theworkers, machines, products, etc., are relatively fixed. Second, the workingprocesses in the industries are already established. For example, in a man-ufacturing workshop, the operating steps, sequence, and the involved tools,machines are pre-specified. In other words, the whole process is known. Atlast, the purpose of each operation, the usage of each component, and the re-quest information of each procedure are all determined. Overall, it can be seenthat there is few unpredictable event in most of the industrial applicationsexcept errors. Therefore, the acquisition system can use the schedule-baseddeterministic manner to communicate with the objects. In this case, it alsolowers the complexity of implementation and avoids missing objects duringthe operations.

• ReliabilityAnother property of the industrial IoT system is that it demands high relia-bility. When it shifts to rely on the information exchange among the objectswithout manpower, reliable data becomes fatal to promise the normal andefficient operations in the industries. Consequently, failure resistance mecha-nism is the requisite part in the acquisition system. The mechanism should beable to consist of three aspects: data re-transmit, data overload, and objectrecovery. The ability of data re-transmit is used to guarantee reliable messagedelivery during routine operations by enabling re-transmission of the failuremessage. And the data overload is an ability to recognize the emergency orcrucial message and pass it to its destination even the system is operatingat a full-load state. It requires the used protocol of the acquisition systemto specify such messages in an expedited manner. The object recovery isused to deal with system death (object lost). Sometimes, if one node in thesystem is down, the following operation may halt unless the node recovered.


Otherwise the system may lose control of that node, and the following workmay be affected. To resolve this problem, a protocol that supports optimizedcommunication, pre-defined timeout period, and rollback methods is needed.It means that, the communication can skip to the next node without waitingfor the failed node when its response period times up. Meanwhile, the systemcan accept the data from the failed node in a new scheduled communicationturn when the node falls back to a previous state for recovery.

• Latency SensitivityIn the industrial IoT system, real-time response is required in most of the ap-plications. Although compared with some mission-critical applications whichdesire millisecond level, that is 1 ms response, the response delay of normalindustrial applications is up to the hundred-millisecond level [74, 75]. Thegreat challenge of latency performance in the acquisition system refers to themultiple objects in one operation. That is, the protocol has to promise theaverage latency of all the involved objects to obtain a short-delay level. Along delay of one object in the operation may result in a long system latency.

• Deployment and DevelopmentAs there are multiple gateway devices to handle the objects in the acquisi-tion system. The diversity and variability of industrial applications requestthe acquisition system to be deployable and expandable for the quantity andinformation type change of the objects. For example, the industrial environ-ment usually has multiple floors and workshops. And one object may moveamong different places and change its role in different areas. If all the areasare managed by one gateway device, it should be able to switch to accept dif-ferent data types of the object in different areas. In addition, the protocol forthe system is required to be capable of adapting the varying system capacity.

• Quality of ServiceThe quality of service in the industrial IoT system can be considered as thecontainment of supporting flexible qualities according to different applica-tion requirements. Additionally, response delay, energy consumption, andcommunication reliability are the major concerns of the service quality, theacquisition system needs to be able to boost the corresponding performanceon demand of the requirements.

2.2 Industrial IoT System

2.2.1 Acquisition System TopologyVarious enabling system topologies used in the acquisition system can be catego-rized into four basic types, point-to-point topology, star topology, bus topology,and mesh topology.

2.2. INDUSTRIAL IOT SYSTEM 15

(a) point-to-point (b) bus (c) star

(d) extended star (e) distributed star (f) mesh

Figure 2.3: Basic system topologies.

Point-to-Point Topology

A point-to-point network [76] shown in Figure 2.3(a) is the simplest structure whichhas a direct connection between two nodes, such as an object and a gateway. Be-cause communication is limited between the two connected nodes, this kind ofsystem can hardly be scaled for a large amount of objects and long operation dis-tance.

Bus Topology

The bus topology [76] as shown in Figure 2.3(b) relies on a single cable, namedbus, to connect a server (a terminator) and multiple nodes. Data travels in bidi-rectional along the bus until it finds the recipient. Because the bus topology onlycommunication through a single bus, the whole network crashes when it fails, andthe network scale is limited by the bus.

Star Topology

The star topology [76] consists of a master node (server or gateway), and a setof slave nodes that are connected to the master node as shown in Figure 2.3(c).The master node acts as a common connection point for the connected slave nodes.All the slave nodes can interact with the master node by sending data to it andreceiving data from it. In this topology, the slave node can communicate withothers through the master node by considering it as a hub.


Similar to the point-to-point network, data packet travels directly between themaster and slave or maximum two hops to reach its destination. A high-throughputlow-latency performance can be achieved using this network. Additionally, eachslave node is independent and isolated to the other slave nodes. This makes thesystem more reliable by simply ignoring the error nodes from the network. However,because the whole connection is master dependent, the system fails once the masternode meets failure or interruption.

Based on the star topology, as can be seen from Figure 2.3(d) and 2.3(e), anextended star topology and a distributed star topology are available [76]. The ex-tended star topology has the ability to cover a larger distance by adding repeatersto build a star link between the master nodes and a higher level node. The extendedtopology is also referred as a hierarchical star topology. The distributed star topol-ogy connects multiple independent star networks. One of the master nodes of thesenetworks is considered as the central node. It can also extend the system’s coverage.

Mesh Topology

Figure 2.3(f) is a basic mesh topology network [76]. In the mesh topology, threetypes of nodes exist: a gateway node performs like a master node in the startopology, router nodes that can both capture/disseminate their own data and actas the routers for other nodes connected to them, and simple nodes which onlyhave data capture/dissemination capabilities. Thus, each node of the mesh systemis connected to more than one nodes. A data packet generated by one node maypass through multiple nodes to reach its destination.

It is obviously that by using the multi-hopping mechanism, the system basedon the mesh topology can work in a long range and large area compared withother topologies. As the path of data transmission is not fixed, the mesh topologyfeatures self-healing to re-route the data path once a failure occurs in its originalroute. This flexible configuration also enables free quantity change of nodes in thenetwork. However, the multiple hopping transmission of data undoubtedly resultsin high network latency and low communication reliability. And collisions and cor-ruptions are unavoidable under the condition of high latency. The system/protocolcomplexity is thus extremely increased when there is a large number of nodes whichall demand a reliable access.

2.2.2 System Topology for Industrial IoT

Among the topologies, the extended star based architecture as shown in Figure 2.4is considered as one of the most practical topologies for the industrial environment.A point-to-point link is built between the objects and the gateway device to ensurethe direct communication. Although it faces some disadvantages compared with themesh architecture used in the wireless sensor network (WSN). That is, its coveragerange is limited, there is no direct communication between two objects, and the

2.2. INDUSTRIAL IOT SYSTEM 17

end-to-end delay may be large. The advantages of the extended star structureoutperform others in the industrial applications.

Network/Server

Gateway Application/service

Application/service

Application/serviceGateway

Gateway

Objects (sensors&chips)

Figure 2.4: System topology for the industrial IoT.

1. The direct connection between each object and the gateway device avoidsfailures caused by another object in the multi-hop case. It also saves theeffort spent on the computation of optional paths for fault tolerant in themulti-hop scenarios. For failure or error of one object, the gateway can fastlocate and handle it in the extended star system.

2. In this structure, the schedule based protocol is easier to implement thanthe mesh topology. Because in the multi-hop scenarios, if an optional pathis selected, the scheduled communication may not be the optimized one. Inother words, the latency may increase, and extra computation is required.

3. The information from one object to another is delivered via the gateway de-vice. For two objects that have large physical distance, this delivery methodoffers shorter end-to-end delay then. Additionally, it lowers the complex com-puting and extra energy consumption of the chip attached to each object byavoiding the judgment of each message it received. The power is saved bysetting the chip to the low-power mode when idle rather than receiving andtransmitting data for other objects.


4. The significant merit of the extended star structure is that it is uncomplicatedto implement and simple to extend. The maintenance cost is low for theindustries. And it gives its protocol more space to focus on the improvementof communication reliability and failure resistance. Although the failure ofthe gateway device is fatal for the system, it can be resolved by employingredundant gateway or other methods. The additional cost is low comparedwith increasing the complexity of the whole system.

2.3 RFID System for Industrial IoT

An industrial IoT system is implemented on the basis of a reliable data communica-tion between the physical objects and the gateway device in the acquisition system.Consequently, accurate and reliable technologies used for delivering the informa-tion for such communication become the key enabler of supporting the operationof the acquisition system. Among others, active RFID technologies such as IEEE802.15.4 compliant/ZigBee, UWB, and UHF RFID are more appropriate becausethey are capable of realizing low-power low-cost implementation while promisingthe communication reliability.

2.3.1 RFID ComponentsRFID is formed as a wireless communication technology which uses radio wavesto realize data delivery. A basic RFID system consists of RFID tags and readers.The tag, also known as a transponder, is attached to target item for collecting data(via sensors) and then transmitting it to the RFID reader. The reader is a usedto send commands for interrogating the tags, and receive the data delivered fromthe tags for processing. It works like an access point for the RFID tags so thatthe information of the target items can be available for further applications andservices.

An RFID tag is normally an integrated circuit (IC) chip which is basically com-posed of an RF transceiver and an antenna. Depending on the power solution, thereare three types: passive tags, semi-active tags, and active tags. The passive tag hasno power supply on the chip. It relies on the received radio waves from the reader.Therefore, an RFID system based on the passive tags can perform limited tasksand can hardly support any extended functions or long-distance communication.Such RFID tag is widely used in retail business to replace the conventional barcodethanks to its extremely low-power low-cost solution [77]. The semi-active tag has abattery for routine work of the RFID chip, but it still needs the reader’s power forbroadcasting. It can communicate in a larger area compared to the passive tags,but suffers from limited applications too. The active tag usually uses an externalbattery to fully provide power for the chip. It is thus capable of supporting variousperipheral circuits for extra functions. For instance, it can have storage module tosave more information than the passive tags, or it can support a microprocessor on

2.3. RFID SYSTEM FOR INDUSTRIAL IOT 19

the chip for multiple sensors. The RFID tag equipped with such microprocessor andsensors can then be considered as a smart tag which is able to not only detect, col-lect data from its attached item, but also pre-process the data or perform self-checkbefore and after communication. Consequently, an RFID system implemented bysuch active tag becomes a great candidate for the IoT application.

An RFID reader, similarly, is comprised of an RFID transceiver, an antenna, theInternet or wireless technology interface, and an optional storage, microprocessor,and so on. The RFID reader can communicate with tags within its operation area.It is able to read and write the tags. Depending on the complexity of the reader,it can perform simple or complicated processing of the data for the connectedcomputer/server.

Overall, the whole RFID system can be recognized as a bridge between the targetitems and the service system which needs the information of the targets. It candeliver information for them. So with the help of a network of the computers/serverswhich have readers connected, the IoT can be achieved.

2.3.2 Active RFID Technologies

Figure 2.5: The operating frequency of the IEEE 802.15.4 compliant technologies[78].

RFID can be classified into low frequency (LF), that is 120 KHz to 150 KHz,high frequency (HF), that is 13.56 MHz, ultra-high frequency (UHF), that is 433MHz, 860 MHz to 960 MHz, and microwave that is, 2.45 GHz, 3.1 GHz to 10.6GHz, according to the operation frequency band [77]. The UHF (433 MHz) andmicrowave bands such as the IEEE 802.15.4 compliant industrial, scientific andmedical (ISM) radio bands, ZigBee, UHF RFID and UWB are appreciatable in theactive RFID system.

• IEEE 802.15.4 compliantThe IEEE 802.15.4 is a standard that specifies a low-power low-cost physicallayer and the media access control (MAC) for the wireless link in the 868


MHz/915 MHz and 2.45 GHz bands for industrial applications [79] as shownin Figure 2.5. It can be further used with the 6LoWPAN as a network layer torealize the wireless embedded Internet. It works as a basic protocol standardand permits extension for specifications.

• UWB

The impulse radio UWB (IR-UWB) technology (3.1 GHz to 10.6 GHz) usesultra-short pulses over a large radio spectrum for data transmission. Unlikethe conventional narrow-band communication such as Wi-Fi and UHF-RFIDwhich employs continuous carrier wave for data transmission, the IR-UWBtransmits repetition of pulses in pico-second (ps) to nano-second (ns) level inthe time domain to represent data information. Compared with duty cycle,the pulse duration is quite short. Thus the average power computation forthe same data is reduced. The energy of IR-UWB signal is distributed overan ultra wide bandwidth (> 500 MHz), so it can transmit without interfer-ing with other narrow-band technologies. That is, it is able to coexist withothers by sharing the same spectrum. As shown in Figure 2.6 and Figure2.7, the UWB can share the same advantage of the expanded bandwidth asthe spread-spectrum technology. But since the large bandwidth of the UWBsignal is generated by the short duration of the pulse, it also enables precisetime-domain resolution. This makes the UWB a good candidate for accuratepositioning based on time-based solutions [80].

Figure 2.6: Pulses and spectrum of the UWB signal compared with the conventionalsinusoidal narrow-band signal.

2.3. RFID SYSTEM FOR INDUSTRIAL IOT 21

Figure 2.7: The coexistence of the UWB and other technologies.

Figure 2.8 exhibits a development map of the RFID technology [81, 82] from thefirst generation which can only perform identification to the fourth generation andfifth generation which enable active and powerful RFID devices for extra computingand networking operation for acting as smart devices.

1st Gen

2nd Gen

3rd Gen

4th Gen5th Gen

• Identification

Passive/backscatter

• Anti‐collision• Re‐writable

• Sensing • Simple data processing• Power management

• Remote monitor• Multi‐ sensing• Extra‐computing• Fine power management• Localization

• Smart ubiquitous device• Monitor/track/control/identify/sense• Fault tolerant• Network support• Accurate positioning capability• Multi‐core multi‐antenna multi‐chip

Antenna

PassiveSemi‐passive

Active

Active/self‐adaption(power compensation)

Time

Complexity

Figure 2.8: Development of the RFID towards the industrial IoT and Industry 4.0.


2.4 Protocols and Standards

Numerous standards are proposed to facilitate the implementations of the IoT sys-tem. For example, Internet Engineering Task Force (IETF), Institute of Elec-trical and Electronics Engineers (IEEE), EPCglobal, 6LoWPAN, and EuropeanStandards Organizations like European Telecommunications Standards Institute(ETSI), European Committee for Standards and so on. They provide protocolsfocusing on the whole IoT applications from the physical (sensor device) aspectto the application aspect. Table 2.1 illustrates some of the common standards insupport of the IoT [83–86].

Table 2.1: The standards proposed for supporting the IoT.

Service Layer CoAP, MQTT, XMPP, AMQP, TLS/SSL, HTTP, DNS, MODBUS, etc.

Network Layer 6LoWPAN, IPv6, IPv4, TCP, UDP, DTLS, etc.

Object Layer IEEE 802.15.4 MAC/PHY, IEEE 802.11, Ethernet (IEEE 802.3), Wireless LAN, PLC, UWB, Z-WAVE, etc.

The protocol which is used for establishing the object communications, that is,the link layer (MAC) protocol for the RFID system, dominates the physical-basedindustrial IoT system. The link layer protocols are generally categorized threegroups, contention-based, contention-free and hybrid.

Contention-based

The contention-based protocols are implemented based on either synchronous orasynchronous transmission schedules. The nodes, that is the objects, contend forthe channel access in various ways to acquire and transmit data depending onthe protocols. All contention-based protocols are intending to improve the delayperformance.

For example, the protocols based on ALOHA and slotted ALOHA [87] aimingto promise a channel access of each node as fast as possible. The drawback of thiskind of protocols is the low throughput which is limited by the high collision ratesince the nodes using these protocols apply a random mechanism to obtain thechannel access. Another cluster of contention-based protocols is developed basedon the S-MAC protocol, such as S-MAC-AL [88], DSMAC [89], energy-efficientMAC [90], and carrier sense multiple access (CSMA) [91, 92] protocols. In these

2.4. PROTOCOLS AND STANDARDS 23

protocols, either adaptive active period is adopted to reduce the forwarding delayor path-aware transmission schedules are employed to achieve an optimal delay.

Contention-free

In contrast to the contention-based protocols, the contention-free protocols rely onthe strictly scheduled coordination of all nodes to eliminate the collision issues inthe network. The contention-free protocols can hardly achieve the minimum delaybut they can potentially provide a bound of transmission delay for all nodes, thusenabling a guaranteed overall delay performance.

Time division multiple access (TDMA) and frequency division multiple access(FDMA) are two common techniques for transmission schedule-based protocols. Inaddition, relying on the basic TDMA and FDMA techniques, dedicated hardwareand multiple channels are employed in some protocols to achieve network-widesynchronization, high throughput and guaranteed delay, such as RT-Link [93] andHyMAC [94].

Hybrid

The hybrid protocol combines two or more protocols to take advantage of themaiming to improve both the performance of delay and reliability.

For instance, the CSMA-TDMA hybrid protocols [95, 96] employs contentionmechanism at the node access phase, and then uses scheduled communication of theaccessed nodes. Although the protocol reduces the contention probability for higherthroughput, it incurs extra delay and energy consumption compared with the pureTDMA protocol. A contention-FDMA protocol [97] further introduces frequencydiversity to enlarge its scalability. It employs one of the available channels as a con-trol channel, and similar contention-to-schedule mechanism in each time intervalsas the CSMA-TDMA protocol for communication. Although the contention-FDMAaddresses better bandwidth utilization, the overhead and uncertainty of access stillexist.

Additionally, many protocols employ mechanisms such as ARQ, power control,and path control to support QoS performance in terms of transmission delay, reli-ability and energy consumption [98, 99].

Protocol for RFID System in Industrial IoT

Overall, considered the property of determinacy of the industrial IoT and its high-reliability requirement, the contention-free protocol is a proper candidate. Al-though, the schedule-based suffers limited latency sensitivity, it can provide apromised delay bound for all the connected objects. This reliability-aware meritoutperforms others in the industrial situations. Besides, certain improvement tech-nique or algorithm can be introduced in the contention-free protocol to minimizethe latency in the applications with the high real-time request.


2.5 Summary

In the chapter, the basic architecture of the industrial IoT system is introduced.The acquisition system, that is the RFID system, which consists of the objects andthe gateway devices, takes care of the information collection, exchange, and controlof the Object Layer, is the basis for the implementation of the industrial IoT sys-tem. Based on the characteristics of the acquisition system, the appreciated systemtopology, communication technologies, and protocols are discussed in this chapter.As a result, the extended star topology, the RFID technology with active RFIDtags, and a contention-free based protocol are recommended for realizing the ac-quisition system in the industrial environment to guarantee reliable, deterministic,real-time, deployable, and QoS performance.

Chapter 3

Reliable RFID CommunicationSystem with QoS Capability

3.1 Background

The RFID system in the industrial IoT application is expected to execute functionsof tracking, monitoring, and control. In the tracking application, the system mas-ters the objects’ position information and moving trace via the data sent from theattached RFID tags. This function is widely expected in tools/components trackingin production plant [100, 101] and people/assets positioning in dangerous workingenvironment [65, 102]. The monitoring function is focusing on the sensing informa-tion of the objects’ working environment and individual status. For example, airquality monitoring can help in the protection of food, animals, plants and people[103–105]. Automated remote monitoring of body condition is highly demanded infuture healthcare industry [106]. And in the control oriented application, the RFIDtechnology is expected as an important pattern in the mass customization manufac-turing industries [107, 108] and the non-mission critical interactive-based operationswhere communication delay is around hundreds of milliseconds [109, 110].

3.2 Proposed System

In view of the characteristics of both the IoT and the industrial environment, wepropose an RFID system aiming to support both the hardware flexibility and thecommunication reliability while minimizing the energy and time consumption.

3.2.1 System ArchitectureAn RFID system architecture proposed for the industrial IoT application is shownin Figure 3.1. In the local area, a server is used to advanced process and store thedata in consideration of the security and confidential requirements in the industrial

25

26CHAPTER 3. RELIABLE RFID COMMUNICATION SYSTEM WITH QOS

CAPABILITY

environment. The RFID readers and the local server are then connected through theEthernet for data interaction within an Intranet [111]. The system can be dividedinto several sub-systems for large coverage. In each sub-system, a transmitterworking as a coordinator, and a cluster of receivers working as the reference readersare employed instead of a conventional gateway.

Local Server

Coordinator

Reader1Reader2

ReaderL-1

tag_11

tag_12 tag_21tag_22 tag_L-1,1

tag_L-1,2

. . .

. . .. . .

Distributed RFID tags

Sub-system

Local operatorsComputers/users

Internet

Sub-systems

Ethernet

Figure 3.1: The proposed system architecture. Adapted from Paper I

The system topology as shown in Figure 3.2 is similar to an extended star topol-ogy. Each central coordinator together with its corresponding reference readers isconsidered as a sub-network inside the local server covered area. And the multiplereference readers in each sub-network enable flexible hardware implementation atthe sensor/tag side. That is, the system can support multi-channel transceiversand multiple technologies simultaneously. The system scalability is physically en-larged by this architecture. Compared with the number of reference readers, thereis a single coordinator in each sub-system. This structure provides a centralizedmanagement of the sensors/tags in each sub-system at the cost of limited capacityat the control link under the scenario of single coordinator and multiple referencereaders. It is feasible to most of the monitor-based industrial IoT applications suchas identifying people, tracking assets, and sensing environment status.

To support both the RFID and the Ethernet communication, the coordinatorand the reference readers all consist of both an RFID interface and an Ethernetinterface. For sensors/tags, each of them is composed of a microprocessor, oneor multiple RFID transceivers, and optional sensors depending on the operation

3.2. PROPOSED SYSTEM 27

Central reader

Reference reader

Target tag

Figure 3.2: The topology of the proposed system.

environment.

3.2.2 MAC Protocol

Based on the system architecture and the characteristics of industrial IoT appli-cation, a contention-free MAC protocol using the multi-frequency TDMA (MF-TDMA) scheme is designed as shown in Figure 3.3. The protocol relies on the timeschedule of the TDMA and employs multiple frequency channels for communica-tion between the tags and the coordinator/readers. In the protocol, a frame cycleis defined as the period that all the tags have finished their scheduled transmission.And each tag is working in a duty-cycle manner for both transmission and receptionto reduce power consumption [111, 112].

Specifically, it can be considered that the protocol provides a multi-channel full-duplex communication capability. That is, an independent channel is allocated toeach reference reader and the coordinator. The whole sub-system uses one dedicatedchannel controlled by the coordinator to pass data from the coordinator to the tags.And multiple channels pre-allocated to the readers are used to transfer data packetsfrom the tags to the reference readers. Each tag can work in at least two channels,one is the dedicated control channel which is fixed for the coordinator, and the otheris the transmission channel. One tag can occupy one or more channels to transmitdepending on the number of transmitters and the initial channel allocations [111,112].


CAPABILITY

masters

CH1

CH2

CH3

CHL-1

timeSlot1

. . .

. . .

. . .

. . .

. . .

. . .

. . .

. . .

. . .

. . .

tag(L-1,1)

. . .

. . .

. . . . . .

frequency

frame cycle

tag(L-1,2)

tag(L-1,4)

tag(L-1,3)

tag31

tag12

send

tag32 tag3mtag33

tag11

tag31 tag32 tag33tag35 tag3m

tag22

tag14 tag12

tag23

tag(L-1,1)

tag(L-1,m) tag(L-1,2)

tag(L-1,3)

tag(L-1,4)

tag(L-1,m)

frame cycleSlot3Slot2 Slot4 SlotM

CHL(syn) . . . . . .

tag21

tag13

tag23

tag21

tag33tag12tag11

tag22 tag23node22

tag31

tag(L-1,4)

Listen(CH1~CHL-1) Listen(CH1~CHL-1)

Figure 3.3: An overview of the proposed MF-TDMA protocol. Adapted from PaperII

3.2.3 SynchronizationSince the time schedule based protocol is sensitive to clock alignment. A synchro-nization mechanism is designed to reduce the probability of collision caused by clockshifts of the distributed tags.

In each scheduled time slot, a guard time is reserved to tolerate the clock shiftsof the tags transmitted at the adjacent slots. As shown in Figure 3.3, althoughthe guard time is used, synchronization of the clocks is required since when theaccumulated clock drifts exceed the bound it can tolerate [112]. A synchronizationcycle tsyn is assumed to constraint by

m · (α+ 2ϕ) ≤ tsyn ≤ ϕ

2εf,max(3.1)

where εf,max is the maximum average drift rate under frequency f , ϕ is half ofthe reserved guard time between two neighboring time slots, α is the effectivetransmission time of one tag, α+ 2ϕ equals to the length of time slot, and m ≥ 1 isa factor that indicates the minimum synchronization interval according to differentapplication requirements [113].

Based on the system structure and the characteristics of the MF-TDMA proto-col, each tag can enjoy an independent synchronization interval besides a universalsynchronization manner. This enables an adaptive synchronization mechanism ofthe tags according to their unique behaviors. Therefore, both uniform synchroniza-tion and independent synchronization are available for the tags.

3.2.4 Optional ARQTo improve the reliability of each transmission, an optional ARQ is used in theprotocol. That is, the tags turn to reception mode for receiving the ARQ packetright after each transmission period as can be seen in Figure 3.4. An ARQ packet


is sent to the tag if its data is not successfully delivered. The ARQ packet indicatesthe time of re-transmission and other relevant information for the tag. On contrast,if the transmitted data of one tag is correctly received by the reader, there is noARQ generated for the tag. The tag turns to sleep when the timeout limit forthe ARQ packet reaches. Since there may exist multiple transmission channels,multiple tags are waiting for the ARQ packet at the same time. The informationfor these tags can be combined in one ARQ packet to promise every failed tag canreceive it before the time runs out.

tagi1

tagi2

tagi,m

no ARQ

ARQ

ARQframe

. . .

guard

guard

guard

Trans

Trans

Trans

Rec

Rec

Rec

Time out

CH i

Figure 3.4: The ARQ method: ARQ for the tags allocated to the same transmissionchannel. Adapted from Paper I

3.2.5 PacketThe packet format of the protocol as shown in Figure 3.5 is similar to the formatused in the IEEE 802.15.4 protocol. It contains a 4-byte preamble, 1-byte StartFrame Delimiter (SFD), and 1-byte MAC length indicator for the physical header.And the MAC packet consists of MAC control word, source/destination address,payload data, and the CRC [111]. The MAC control word (1 byte) is used toindicate the packet type as illustrated in Table 3.1.

Payload CRCSrc Dstpreamble SFD Len Con

4 1 1 1 0~8 0~8 20~108MAC

PHY

Figure 3.5: The packet format.Adapted from Paper I


CAPABILITY

Table 3.1: The MAC control word. Adapted from Paper I

We first plot the average drift in different drift

rate in Fig. 4. Based on our simulation, the average drift ∆

is not impacted by slot length, guard time and

frame cycle. It increases almost in linear as the maximum drift rate , it is 0.41 us/s at 20 ppm and 2.88 us/s at 140 ppm as shown in the figure. However, since the clock drift of one node can be either positive or negative, the accumulated drifts of the node in one frame cycle do not apply to the linear law. In the worst case, if the

clock drift in the same direction during the whole frame cycle, a guard time of 0.41 us is expected to tolerate the node whose clock has a maximum drift rate of 20 ppm under 1 s frame cycle.

Length of data packet 16 bytes/128 bytes Update (duty) cycle 1 s/10 minutes

Symbol rate 64 kbps/1.6 kbps Number of devices 100 ~ 10000

Number of transmission channels 1 ~ 100 Guard time 0.2 ms/120 ms

bit Control word Description 7 default: 1 1: data pkt

0: non-data pkt 6~5 default: 00 11: broadcast sync pkt

10: sync pkt 0x: non-sync pkt

4 default: 0 1: control pkt 0: non-control pkt

3~2 default: 00 11: single ARQ pkt 10: multiple ARQ pkt 0x: non-ARQ pkt

1~0 default: 00 reserved

Fig. 1. Average drift rate

∆ under different maximum drift rate

20 40 60 80 100 120 1400

0.5

1

1.5

2

2.5

3

Drift rate (ppm)

Ave

rage

dri

ft (

us/

s)

Four types of packet is employed in the protocol:

1. Data packet. It is the packet sent from the tags to the readers. It should atleast contains its own address for the readers to match with the schedule map.If the received data is transmitted from a tag not scheduled, the data packetwould be dropped and then a synchronization message including schedulecorrection may be sent to the tag.

2. Synchronization packet. There are two synchronization methods: the uniformand the independent. A broadcast packet is employed in the uniform synchro-nization. All the tags can receive this packet if they are in the reception mode.In this case, no destination address is required in this synchronization packet.The source address is optional since the synchronization time is appointed.For the independent synchronization, its packet is sent together with the ARQpacket or control packet. No dedicated independent synchronization packetis recommended in the communication.

3. ARQ packet. If the ARQ packet has only one destination, the correspondingaddress is explicit shown. Otherwise there would be no data in the addressfield. Both the destination and re-transmission information are written in thepayload in serial format. The tags need to recognize their own informationaccording to the addresses. And the tags can tell which type of ARQ packetit is according to the MAC control word.

4. Control packet. This packet is sent from the coordinator to the tags.


3.2.6 Slot Allocation

The slot allocation in each transmission channel is independent, that is, there can bea diverse number of the slot with different period length in each channel. A flexibleslot allocation is then available for the tags in each coordinator controlled sub-system. The assigned slot for one tag can be moved from one transmission channelto another or from one sub-system to another on demand of the requirement whenidle slot exists.

3.2.7 Communication process

There are 5 timers working in each tag, a transmission timer, a synchronizationtimer, an ARQ timeout timer, and a re-transmission timeout timer [111].

The transmission timer stores the time point of transmission of one tag in eachupdate cycle. It is scheduled according to the transmission map generated by theserver and assigned to the tag at the initial stage of the whole communication(including each initialization of the system refresh).

The synchronization timer is used for listening to the broadcast synchronizationmessage. If a synchronization packet is received individually (from control/ARQpacket) before this timer reaches, a new timer is set according to the informationof the received synchronization packet. Otherwise, the synchronization timer resetsautomatically after the synchronization.

The ARQ timeout timer is used to record the maximum ARQ waiting periodafter the tag’s transmission. If one tag does not receive ARQ packet within thisperiod, it turns to another state such as sleep.

The re-transmission timeout timer indicates the maximum reserved time lengthfor re-transmission in each transmission channel. It relies on the idle time betweenthe end time of the frame length and the update cycle.

Flow of Tag

As illustrated in Figure 3.6, for each tag, the transmission timer equals to its indi-vidual update cycle (it may not be the same as the others). And the ARQ timeouttimer is set every time when the transmission is complete. The control timer andthe synchronization timer may be much larger than the transmission timer. Thesynchronization timer can be modified if an independent synchronization messageis sent together with an ARQ packet.


CAPABILITY

start

Tx timer reaches?

Pkt in Tx buffer?

Add src&dst addrThen, Tx

Tx finishes?

Turn to Rx

ARQ time out?

Turn to sleep

Pkt in Rx buffer?

Re-transmit time out?

Delete Tx pkt, reset Tx timer

and ARQ timer, sync

clock (if sync data Rx)

Refresh ARQ timer, Tx timer

Control timer reaches?

Sync timer reaches?

Turn on Rx

Rx finishes?

Set e.g. clock, task, timerDelete Rx pktTurn to sleep

y

n

n

y

n

y

n

y

n

y

y

n

y

y

y

nn

n

Figure 3.6: The flowchart of a tag in the communication process. Adapted fromPaper I


start

Pkt from server?

control pkt?

ARQ pkt? Multi-ARQ?

Broadcast?

Add dst addr

Re-organize payload

y

n

y

y

y

Tx finishes?

y

n

Timer reaches?

Delete pkt

Tx

n

n

n

y

y

n

y

Figure 3.7: The flowchart of the coordinator in the communication process. Adaptedfrom Paper I


CAPABILITY

Flow of Coordinator

Figure 3.7 is the flowchart of the coordinator. During the communication process,the coordinator only in charge of sending control packet, ARQ packet and synchro-nization packet to the tags. All these packets are generated or triggered by theserver according to the received results from the reference readers. For example, ifone reader reports the failure of reception of one tag’ data, the server then generatesa re-transmission schedule and sends it to the coordinator. To guarantee the syn-chronization of all the sub-systems and enable flexible moving from one sub-systemto another, the system selects the server’s clock as the reference clock.

3.2.8 Protocol Implementation

The implementation of the designed MF-TDMA protocol can be divided into fourphases as described in Figure 3.8. Phase 1 is a downlink, that is from the coor-dinator to the tags, at which the coordinator sends initial information or controlcommands to the tags. And Phase 2 is an uplink, that is from the tags to the read-ers. In this phase, the tags transmit sensing/identifying data or response report tothe readers based on the received orders of Phase 1. Phase 3 is also a downlink.The tags may receive feedback packets containing error control message such as theARQ and commands regarding the state of the delivered data from Phase 2. AndPhase 4 is employed for those tags which have received a message at Phase 3 toresponse according to the error control.

Phase 1 DownlinkSend command

Phase 2 UplinkListen

Phase 3 DownlinkSend ARQ/Sync/

Error control

Phase 4 UplinkListen

Tra

ckM

onit

orC

ontr

ol

listen

send

idle

Sendsuccess

Error

ARQ

Sync

Errorcontrol

......

...

...

...

... ...

...

...

... ...

...

Bursterror

1 2 3 4 5 6 7

8 9 10 12 13 1411

4

4 5 6 7

8 12

Figure 3.8: Four-phase communication process of the MF-TDMA protocol.Adaptedfrom Paper III

3.3. QOS PROTOCOL IMPLEMENTATION 35

3.3 QoS Protocol Implementation

3.3.1 MF-TDMA for Energy-constraint Monitoring

The monitoring focused industrial application normally features long data updatecycle and diverse update packets depending on different types of sensing informationand objects. Energy consumption which determines the RFID tags’ lifetime is thenthe key issue in such RFID system.

ARQ

sync

Cnd(dl)

ch1(ul)

chL(ul)

1 2

3

2

3

1

update cycleInitialization

command

ARQ timeout

ARQ received re-transmit

(dl)

(dl)

sensing pkt idle period

slot for tagi(ul) slot for tagj(ul)

slot for tagi(dl) slot for tagj(dl)guard

Figure 3.9: Protocol description for the energy-constraint monitoring application.Adapted from Paper III

Figure 3.9 illustrates how the proposed MF-TDMA protocol implements in suchmonitoring applications. It shows a multi-channel implementation, that is, the tagsare allocated to transmission channels from ch1 to chL, and the Cnd is the ded-icated command channel. Phase 1 as shown in Figure 3.8 is the initial stage forthe coordinator to confirm the schedule arrangement with the tags. And this phaseis not repeated during the monitoring operation until an appointed system refreshtime. The time slot and transmission allocation are pre-defined according to theupdate cycle of each type of tag to promise all the transmission channels sharing thesame frame length. This frame length can be considered as the system update cycle(time period that tags in each channel finish their transmission without consideringre-transmission). The frame length is set smaller than the tag’s update cycle. Anidle period is reserved between the end of transmission of the last tag of the previousframe, and the start of the following frame. During this idle period, the tags whichreceived an ARQ packet re-transmit their sensing data accordingly (Phase 3). If onetag still fails to deliver its sensing packet and the re-transmission timer is available,another re-transmission time can be sent via a new ARQ packet. It can re-transmitthe packet again. The length of this idle period is the maximum length bound ofthe re-transmission timer. Considered the characteristic of the monitoring applica-tion, both the broadcast synchronization and the independent synchronization canbe used. The broadcast synchronization packet is recommended for reducing theimplementation complexity and energy consumption.


CAPABILITYUpdate cycle

tguardttrans

CHi

t trans

CHi

Update cycle

Update cycle Update cycle

m cycles

n cycles

n>msync

original

optimized

Figure 3.10: Optimization of the guard time and transmission time in each slot forreducing the synchronization rate.

By minimizing the average transmission and reception period, it can furtherreduce the energy consumption of each tag. Figure 3.10 describes an exampleof a transmission period and synchronization rate reducing method for the tagswith temperature sensors for fruit status monitoring in a warehouse. Assumingthat the sensing payload is 12-bit length (−55◦ ∼ +125◦ with 0.1◦accurancy) andthe temperature update interval is 10 minutes. Then based on the applicationenvironment, it is feasible to reduce the payload to 8 bits for indicating ±10◦variations compared with the previous update. Therefore, as shown in Figure 3.10,instead of transmitting a full sensing packet (ttrans), the tags can transmit a reducedpacket within t′trans. Under the same time slot allocation and required systemupdate rate, larger guard time t′guard is achieved between two slots. The broadcastsynchronization interval can be then enlarged from m cycles to n cycles.

3.3.2 MF-TDMA for Latency-constraint TrackingOn the other hand, the tracking focused application is sensitive to delay ratherthan energy when a continuous tracking is desired for moving objects.

Figure 3.11 is the proposed protocol implementation for latency-constraint track-ing applications. In this implementation, payload length of position information isassumed to be the same for different tags. To achieve the minimum system latencyfor frequent position update of each tag, the system update cycle is set to be equalto the frame length (the maximum frame length of all the used transmission chan-nels). Hence, the re-transmission mechanism and the broadcast synchronizationare not employed due to the limited idle period between two update intervals. Inother words, the tags do not need to turn to reception mode after each transmis-sion for the ARQ packet. And independent synchronization message is sent for eachtag with possible control information. Moreover, as can be found from the figure,various guard length is used for the tags, that is, there exists diverse slot length


sync update cycleInitialization

command

position pktCnd(dl)

ch1(ul)

chL(ul)

(dl)

(dl)

slot for tagi(dl)

guardslot for tagi(ul)

Figure 3.11: Protocol description for the latency-constraint tracking application.Adapted from Paper III

0 2 4 6 8 1010

-2

10-1

100

Time (year)

Ene

rgy

cons

umpt

ion

(Ah)

full pkt (energy)full pkt (latency)reduced pkt (energy)reduced pkt (latency)

200 mAh battery with 5% leakage per year

100 mAh battery with 5% leakage per year4*10-2

Figure 3.12: Estimation of energy consumption of both energy-constraint andlatency-constraint scenarios. Packet length: 60 bytes, reduced packet: 40 bytes,update cycle: 10 minutes, current for transmission, reception and sleep: 30 mA, 15mA, and 1 µA, synchronization interval: 37.5 minutes and 28 seconds.

in each frame. This various guard length enables different synchronization intervalamong the tags. Similar to the energy-constraint monitoring, reduced length ofposition packet can be used to further decrease the transmission delay and powerconsumption.

Figure 3.12 shows a comparison of energy consumption of the tag’s RF mod-ule working in the energy-constraint scenario and the latency-constraint scenario,respectively. In this figure, the following assumptions are made: the packet length


CAPABILITY

for both scenarios is equal, that is 60 bytes, and the transmission period is around50 ms at 10 Kbps rate. The reduced packet is 40-byte length, and the tag’s updaterate is every 10 minutes. No ARQ or re-transmission is used. The average currentconsumption of transmission, reception, and sleep is considered as 30 mA, 15 mA,and 1 µA, respectively [114, 115]. Different guard length is used for the tag work-ing in the energy-constraint scenario and the latency-constraint scenario to support37.5 minutes and 28 seconds synchronization interval, respectively.

It can be seen, under the same condition, when enlarging the guard lengthto 9 times of latency-constraint scenario for the energy-constraint application, itconsumes about 60% less power. And the lifetime of the tag extends to 5 years fromabout 2.2 years. When a reduced packet is used, it can further reduce 20% powerconsumption for the energy-constraint application in this case (from 60 bytes to 40bytes).

For latency-constraint applications, the queuing time of each tag which is thedelay from packet generation to packet transmission also affects the performanceespecially in the time schedule based protocol scenario. In the proposed MF-TDMAprotocol, each tag can only transmit at the slot assigned to it at each update cycle.Hence, if the assigned slot is earlier than its packet generation time, the transmis-sion may fail and a re-transmission requires. Alternatively, it may transmit thepacket generated at the previous update cycle at this time without re-transmissionorganized. On the other hand, if the assigned slot is quite late compared to thepacket generation time, a long queuing time is also introduced.

Therefore, a slot allocation optimization as shown in Figure 3.13 is designed tohelp to improve the slot allocation according to previous performance of each tagto minimize the queuing delay. It can be described as

• The packet of tag p generates before its assigned slot: Assume that slot tTS,pis assigned and tg,p is its packet generation time. The optimization process isto exchange tTS,p with (or move to a slot if it is idle) an available closer timeslot tTS,p′ ∈ (tg,p, tTS,p].

• The packet of tag p generates after its assigned slot: Similarly, the optimiza-tion for this case, new time slot tTS,p′ ∈ [tg,p, tframe) is selected from the endof its packet generation time to the end of the frame.

This optimization is executed based on an assumption that the packet generationtime of each time is a random event at the first time. And then the packetsgeneration follows the duty-cycle principle.

We predict the packet generation time by a Poisson Distribution,

pn(t) = e−λt(λ)n

n! (3.2)

where n is the number of packet generated at time point t, and the interval ofpacket generation can be expressed as

P0(t) = e−λt (3.3)


pkt gen

frame re-trans

delay guard

duty cycle

initial allocation

optimized allocation

Figure 3.13: Optimization of the slot allocation for reducing queuing time for trans-mission. Adapted from Paper I

It indicates that from time 0 to t, no packet is generated. 1/λ is then theexpectation of packet generation interval. Here we define the density of packetin one transmission channel as λ. If λ is large, that is, the expectation of packetgeneration interval is small, which indicates that most of the tags in the samechannel generate packets at a contiguous time. In this case, a long queuing delayis expected in the MF-TDMA protocol due to the scheduled principle. Otherwise,when λ is small, the packet generation time of the tags is distributed over a longperiod, there may exist more space for the slot optimization method to decreasethe queuing delay. Then the packet generation time can be assumed as

tg = − 1λlog(1− 1

λrand(N)) (3.4)

where N is the quantity of tags in each transmission channel.As a comparison, Figure 3.14 and Figure 3.15 draw the statistical results of

the queuing time (waiting time) for the different expectation of density of packetgeneration of 1000 tags allocated in one transmission channel, respectively. Tobetter illustrate the performance of the proposed MF-TDMA protocol and theimprovement after slot optimization, the contention-based np-CSMA [116] protocolis shown as a reference. In the simulation, a 16-byte data packet is assumed for each


CAPABILITY

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Waiting time (s)

0

20

40

60

80

100

120

140

160

180

Num

ber

of tag

(sin

gle

CH

)

np-CSMAinitial MFTDMAoptimized MFTDMA

Figure 3.14: Queuing time for 50 ms (λ = 1/(50ms)) expectation of generationinterval of 1000 tags using np-CSMA protocol, the initial MF-TDMA protocol, andthe slot optimized MF-TDMA protocol. Adapted from Paper I

tag, the data rate is 256 Kbps, the guard length is 0.2 ms, and the data update cycleis every 1 second (the packet generation cycle is assumed to equal to the updatecycle).

It can be seen that, in Figure 3.14 the packet density is large in a short pe-riod. The contention-based np-CSMA method can provide a better performancein queuing delay since the transmission period of each packet is quite short. Itmanages to provide 17% of the tags to transmit within 50 ms queuing time, whichis twice of the number of the proposed MF-TDMA method. For MF-TDMA pro-tocol, it provides a bound of the queuing time at 550 ms and 700 ms depending onif the slot allocation is optimized or not. This is at least 100 ms shorter comparedwith the np-CSMA protocol in this case. And as shown in Figure 3.15, when thepacket density drops to 1/(500 ms), the MF-TDMA protocol with slot optimizationachieves a great progress. It can provide 50 ms queuing time for 60% of the tags,while promising all the tags queuing time no more than 400 ms [111].

When multiple transmission channels are employed, as shown in Figure 3.16and Figure 3.17, the MF-TDMA with slot optimization guarantees less than 100ms queuing time. In the simulation for the two figures, 5 and 6 channels are usedfor the 1000 tags, respectively. For the proposed MF-TDMA protocol, since onechannel is occupied dedicated for control, it employs 1 channel less for transmissioncompared with the np-CSMA protocol. It is shown that although the MF-TDMA


0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Waiting time (s)

0

100

200

300

400

500

600

700

800

900

Num

ber

of tag

(sin

gle

CH

)

np-CSMAinitial MFTDMAoptimized MFTDMA

Figure 3.15: Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using np-CSMA protocol, the initial MF-TDMA protocol, andthe slot optimized MF-TDMA protocol. Adapted from Paper I

protocols use 1 channel less, it can promise almost 100% of the tags to achieve aminimum of 50 ms queuing delay after slot optimization when 6 channels are used.

It can be concluded that with the slot optimization, the proposed MF-TDMAprotocol can provide guaranteed short queuing delay of all the tags for latency-constraint applications. The scheduled transmission also prevent unnecessary col-lisions occurred when using contention-based protocols.

3.3.3 MF-TDMA for Reliability-aware Control

When turning the RFID technology to the control application in the industrial field,cost and reliability are the primary concerns. Under the IoT context, the RFID tagsattached to ubiquitous objects such as raw materials, components, tools, and ma-chines should be able to communicate with the process controller for correspondingexecutions.

Hence, in the control oriented applications, the coordinator is mainly used tosend control commands to the tags. Depending on the objects each tag attached,they either complete the command by showing the identification or forward theorder to its microprocessor to direct other executions of the object. To enablereliable control, execution report is required from the RFID tags which may notice


CAPABILITY

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Waiting time (s)

0

100

200

300

400

500

600

700

Num

ber

of tag

np-CSMA(5CH)optimized MFTDMA(4CH)

Figure 3.16: Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using 5 channels. Adapted from Paper I

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Waiting time(s)

0

100

200

300

400

500

600

700

800

900

1000

Num

ber

of tag

np-CSMA(6CH)optimized MFTDMA(5CH)

Figure 3.17: Queuing time for 500 ms (λ = 1/(500ms)) expectation of generationinterval of 1000 tags using 6 channels. Adapted from Paper I


the controller (server) whether the order is carried out successfully or not. If errorsare reported, the server needs to turn to error control to ensure the process.

It is notable that all the actions of the RFID tags rely on the control orders.Normally, one working process can be divided into several independent stages. Andeach stage also includes several actions. Each action may require multiple objects toperform different operations. The whole process is pre-divided into multiple stages.The time period used by executing each stage is defined as a control cycle. Thelength of each control cycle thus may vary. The control cycle is composed of severalcommands. One or multiple objects may collaborate for completing one command.Therefore, in one control cycle, the tags need to know when to start to listen to theircorresponding orders. And then they have to report the operation results to thereaders to indicate if the coordinator can continue to send the following command.Figure 3.18 shows how the protocol implemented for control based on the aboveprinciple. The communication process of the protocol can be described as follows:

commandcontrol cycle

burst error

error control command continue

error resolved

interrupted by error control

error control for normal error

normal error

Cnd(dl)

ch1(ul)

chL(ul)

(dl)

(dl)

success response

slot for tagi-k(dl)

slot for tagi-k(ul)

schedule

wait for next cycle

Figure 3.18: Protocol description for the reliability-aware control application.Adapted from Paper III

• An initial control packet is sent at the start of the whole control process. Itis used to synchronize the tags and assign the schedule map. The tags obtainthe start time of each control cycle from this schedule map and turn on theirreception module at the corresponding time.

• After initialization, the process starts. At the beginning of the control cycle,all the tags receive a command packet which indicates the listening time ofeach tag within this control cycle.

• Then the tags start to listen for commands in turn. When the correspondingtask of one object is accomplished, the tag sends a report to indicate itscompletion state.

• If errors are reported, the server needs to turn to different error handlersaccording to the types of error. In brief, there two types of error. They aredefined as normal error and burst error. The normal error can be consideredas an independent error. In detail, a normal error only affects the object who


CAPABILITY

meets the problem, the other objects can finish their tasks in the control cyclewithout the success of this object. In this case, the server doesn’t handle thisproblem immediately. Instead, it sends a packet including information forerror control, that is an ARQ with the appointed error control time. Theerror handler would be carried out at the end of the whole control cycle whenall the other commands are completed. Since extra time is demanded for thiserror control and its period is unpredictable. To avoid missing the schedulingof the next control cycle, all the tag needs to turn on the reception modewhen the success report of its last command is sent. For the burst error,the other objects or the following commands cannot be continued when itoccurs. An immediate error handler or manpower is thus demanded. Oncea report of burst error is received, the server lets the coordinator interruptthe current command process to handle it. On the other hand, the objectsinvolved in this error are waiting for the error handler after the burst errorreport. Meanwhile, the timers which are used for record the listening schedulewithin the control cycle are paused for all the involved tags. For the otherobjects which are not involved, they have to keep listening until the end of theerror handler. Additionally, their timers for schedule can be updated by thefollowing commands accordingly to ensure time alignment within this controlcycle.

3.3.4 Throughput and Packet Delivery RatioThe packet loss rate (PLR) is an important factor to measure the communicationreliability. Excluding collisions due to access contention, channel interference isanother element that may generate the packet loss. However, it is inevitable tomeet such interference which is caused by occlusions, metallic items, and othertechnologies compared with the conventional wired methods when using wirelesscommunication technologies in the industrial environment.

Since multiple channels are employed in the proposed MF-TDMA protocol, thetags may suffer from high packet loss if their transmission channel has got strongerinterference than others. Thanks to the flexible and independent tag allocationmechanism among different transmission channels, we are able to assign the tags tothe channel with better performance. However, higher latency is then introducedin this case when the number of tags is fixed.

We use the packet delivery ratio (PDR) and the system throughput to evaluatethe performance of the protocol. The PDR is defined as the ratio of the successfullydelivered packet to the total packets sent.

PDR =∑i=L−1i=1 qi · Pi∑i=L−1i=1 Pi

(3.5)

where qi is the factor of the quality of channel i, it represents the degree of interfer-ence of one transmission channel.

∑i=L−1i=1 Pi is the number of the whole transmitted


500 1000 1500 2000 2500 3000 3500 4000 4500

0.75

0.8

0.85

0.9

0.95

1

Number of tags at the best−performed transmission channel

Pac

ket d

eliv

ery

ratio

500 1000 1500 2000 2500 3000 3500 4000 45002

4

6

8

Thr

ough

put (

pack

ets/

seco

nd)

PDRThroughput

Figure 3.19: The PDR and the throughput curves for different tag allocations.

packets of the tags, and∑i=L−1i=1 qi · Pi is the number of packets received by the

readers through the whole L− 1 transmission channels [112].The system throughput is expressed as the number of packets received within

each update cycle. It depends on both the successful delivery packets and thetransmission delay,

throughput =∑i=L−1i=1 qi · Pitupdate

(3.6)

To observe how the channel performance affects the packet delivery ratio andthe system throughput, an instance under the following assumptions is shown.There are 10 available transmission channels and 5000 tags working in an energy-constraint manner. Each tag requires 50 ms to transmit its data packet, and 450ms guard time is reserved for the adjacent transmissions. For simplicity, the 10transmission channels are supposed to encounter the average PLR of 5%, 10%,15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%, respectively. The default updatecycle is 10 minutes, and it can be enlarged up to every 37.5 minutes. Withineach update cycle, at least 10 seconds are reserved for re-transmission and optionalsynchronization. Thus up to 1180 tags can be allocated to the same transmissionchannel when the update cycle is 10 minutes. And this number grows to 4480 fora 37.5-minute update cycle.

The curves are drawn in Figure 3.19, where the greedy algorithm is employedto re-allocate the tags to better transmission channels. When the 5000 tags areequally allocated to the 10 channels, due to the assumed PLR, it obtains the lowestPDR, and the PDR increases as more tags are re-allocated to the channels withbetter quality. For the throughput, when the best channel has less than 1180 tags,


CAPABILITY

the throughput grows as the increase of the PDR. Since more than 1180 tags areassigned to one channel, the increase of update cycle resulting in a decrease of thethroughput correspondingly. Therefore, on demand the QoS requirements of thePDR and the throughput performance, it can always achieve an optimal allocationmethod of different application environments depending on the update cycle, thenumber of tags, and the number of available transmission channels thanks to theflexible allocation mechanism.

3.4 Summary

In this chapter, first we describe an RFID system designed based on a discretegateway architecture and the corresponding MF-TDMA protocol for the industrialIoT. Second, for various QoS requirements, instance designs for energy-constraintmonitoring, latency-constraint tracking, and reliability-aware control scenarios areintroduced based on a four-phase communication process.

The discrete gateway architecture is composed of a coordinator and multipleRFID readers. This structure explicitly separates the tag control and data collectionby employing the coordinator working in a dedicated frequency band. The multipleRFID readers can be distributed to a large coverage to receive data while the centralcoordinator can work in a comparably high power manner to control the tags. Asmentioned in this chapter, this structure also enables multiple RFID techniques tobe used when the tags are equipped with a uniform receiver for listening to thecoordinator’s control.

Based on the system architecture, a contention-free MF-TDMA protocol is de-signed to offer schedule-based communication for applying in the industrial envi-ronment. It can take care of multi-channel communication simultaneously whilesupporting an independent control channel for all the tags within one gateway’scontrol area. To handle the latency and reliability demands, an optional ARQ,independent/uniform synchronization and control mechanism, as well as a slot al-location optimization algorithm are used. With the help of these methods, the pro-tocol can provide high communication reliability and low transmission delay withguaranteed delay bound as illustrated in the instance simulations in this chapter.

To explain how to support the QoS performance, the communication processof the system is summarized in four phases. Examples for different performancerequests are shown independently according to the four-phase communication stage:

For application with the energy-constraint requirement, a various length oftransmission packet enables flexible slot allocation for sensing tags with differentfunctions. With the help of the re-arranged slot length for the reduced packet,it can be optimized to enlarge the guard length for longer synchronization cycleand decrease the turn-on time of the tag’s RF module. The power consumption isthus further reduced. Additionally, in the energy-constraint applications, there maybe a long idle period before a new update turn, synchronization at the broadcastmanner can lower the implementation complexity compared with the independent

3.4. SUMMARY 47

synchronization manner. It is notable that the update interval may be large in suchapplication, the ARQ mechanism, on the other hand, provides high transmissionreliability.

For the aspect of the latency-constraint tracking applications, the long queuingtime is a fatal defect of the schedule-based protocols which restricts fast access ofthe packets. In our design, the server presumes the packet generation time based onthe previous transmission delay of each tag, and re-allocated the tags to new trans-mission slots to decrease the queuing time. With the help of the optimization, thesmaller average transmission delay of each tag and smaller access latency of eachtransmission channel are achieved. Furthermore, the employment of parallel trans-mission of multiple channels can improve the optimization by re-allocating the tagsto the new transmission channels for reducing queuing time. On the other hand, ineach update cycle, various guard length is used to compensate the interval betweenthe transmission of two slots resulting in independent synchronization capability.By carrying out such independent synchronization, the server can customize thesynchronization cycle for each tag.

To improve the communication reliability is seriously desired in the control-orient industrial applications. The MF-TDMA supports strict error control mech-anism. Two types of error handler are provided to resolve the error in a real-timemanner or a time-lapse manner depending on its level of effect. Another methodintroduced to improve the reliability is implemented on demand of requirement ofthe packet delivery ratio and system throughput under the consideration of thechannel quality. Different allocation methods can be used to obtain higher packetdelivery ratio or throughput thanks to the flexible slot allocation mechanism.

Chapter 4

2.4-GHz/UWB Hybrid PositioningPlatform

4.1 Background

4.1.1 Context Awareness of the Industrial IoT

The value of location information in the industrial environment lies in the ability notonly to identify and locate any products, machines, and workers, but also to delivertheir information to users or applications for real-time context-aware industrialintelligence. Therefore, the location information for the industrial application isboth accuracy and time dependent.

As the emergence of sensor-based networks and wireless communication solu-tions, real-time location information for indoor environments attracts more atten-tions especially in the industrial applications. The Real-time Locating Systems(RTLS) based on different wireless technologies such as RFID, UWB, ZigBee, Blue-tooth and WiFi, as shown in Table 4.1, towards industrial applications [117–125]can continuously monitor targets to reduce search time and improve operationalefficiency.

4.1.2 Indoor Positioning Techniques

Proximity Detection

The proximity detection provides symbolic location information by cell of origin(CoO) method with known position of antennas. That is, when a target is detectedby one or more antennas, its location is estimated by the one that receives thestrongest signal [126].

X̂ ∈ ‖X − ai‖ < r, where maxi∈Q{RSS (ai)} (4.1)

49

50 CHAPTER 4. 2.4-GHZ/UWB HYBRID POSITIONING PLATFORM

Table 4.1: RTLS solutions. Adapted from Paper IVSolution/System Technology Accuracy

& Reliability

Scalability Maintenance Cycle

System capacity

Cost

AeroScout Wi-Fi (RSS, TDoA)

1 - 3 m < 200 m @ outdoor < 60 m @

indoor

< 4 years @ reduced rate & turned off

>300 persecondper cell

Medium (From

$10 per tag )

Ekahau Wi-Fi(RSS)

1 - 3 m @ RSS>-

75dB

Wi-Fi covered distance

< 5 years @ reduced rate & turned off

>3000eachtime

High (From

$50 per tag)

Awarepoint 1-3 m(bed

proximity)

in-room < 3 years based on

movement detection

N/A Low

Nebusens > 1m@ >-

100dBm

< 500 m Several months

N/A Low

Zebra 0.9 m @ 50 m radius

1.6 m @ 95 radius

120 m @ indoor

1000 m @ outdoor

< 7 years @ 5 days

update rate

300 per second

High (System

begin from

$50,000) Mojix 1 m by

adding eNodes

< 10000 m2

@ 1 receiver &

512 eNodes

Without battery

1200 reads per

second

Low (1/100 cost of active

RFID tag)

RF Controls ± 1’ @ 3-D

& 30 cm

< 100 m Without battery

Depends on the sweep speed

Low

Ubisense 30 cm & 15 cm

@ controlled

area

100-1000m

40m×40m with

standard 4 sensors

4-6 yearsdepends ontag type andlocation rate

Depends on cell

and update

rate

High (Research package

from €17000)

Time Domain

ZigBee/IEEE802.15.4

ZigBee/IEEE802.15.4 (RSS)

Active RFID + IEEE 802.11b

(ToA, TDoA)

Passive RFID

Passive UHF RFID (based on patent-pending BESPA

antenna) UWB

(TDoA, AoA)

UWB(two-way ToA)

2 cm @ LoS

< 50 cm @ NLoS

40-80 m < 4.2 W power

consumption

N/A High

where ai is the position of antenna i which receives the strongest signal from thetarget, and r is the circle of its cell. The location of the target is determined insider.

Triangulation

The triangulation is the basic measuring principle for positioning. It relies on thegeometric properties of triangles to determine the target’s position. Techniquesbased on measurements of distances or angles between the target and known pointslike ToA, TDoA, round-trip time of flight (RToF), received signal strength (RSS)measures the distance either by calculating the propagation time of signal or com-paring the received signal strength with a certain propagation model to locates the

4.1. BACKGROUND 51

target. The angle of arrival (AoA) technique can further estimate the target loca-tion by computing the angle of received waveform relative to the reference points[127, 128].

In the distance measurement based triangulation principle, the location X̂ of thetarget can be estimated using the linear least square (LLS) algorithm by minimizingthe difference between the real distance d and the estimated distance d̂ based onthe position of a known reference,

X̂ = argminX∈R

∥∥∥d̂− d∥∥∥ (4.2)

Fingerprinting

The fingerprinting (FP) method is basically a pattern matching based locationestimation. It includes a calibration phase to build a measurement module/map,either empirically or computed analytically, and an estimation phase to comparethe received signal with the model to determine the target’s position [129].

Dead Reckoning and Kalman Filter

The dead reckoning (DR) method estimates the target’s position by its previous lo-cation and estimated moving speed. A speed sensor may be needed in the operatingprocess, and the positioning error grows as it is accumulated by the former positionestimates [130]. The Kalman Filter (KF) algorithm is widely used for DR-basedlocation estimation by seeking the maximum conditional probability of the target’sstate to predict its position [131].

X̂(k + 1) = Φ[X̂(k), u(k)] (4.3)

where X(k) = [x, y, z, θ] is the target’s position at step k, and u(k) = [d, α] is theestimated input, that is, the target first moves distance d, and then turns an angleα at step k. Its position at step k + 1 can then be estimated by X̂(k + 1).

4.1.3 Accurate Positioning using the UWB TechnologyIn contrast to the conventional narrow-band technologies, the UWB transmitsthe pulses with length from pico-seconds to nano-seconds in a duty cycle man-ner. The ultra-short pulse duration of the IR-UWB signal enables accurate rang-ing/positioning potential of centimeter-level using the ToA-based methods in anindoor environment. The pulses can better resist to multi-path components in thetime domain compared with the carrier-based narrow-band waveforms. In addition,the structure of the UWB transmitter can be realized in a simple and low-powermethod.

In Figure 4.1, a comparison of the performance of tag transmits using the UWBtechnology and other technologies in terms of coverage, data rate, positioning ac-curacy and power consumption is summarized [132–134]. It can be concluded that


31

Cov

erag

e

Data rate1kbps 1Mbps 1Gbps10kbps 100kbps 10Mbps 100Mbps 10Gbps

1mm

1m1c

m10

cm10

m10

0m1k

m

SatellitePositioning accuracy:6m~10m

Active RFID (IEEE 802.15.4/ZigBee)

WiFi (IEEE 802.11)

UWBBluetooth

Passive RFID (UHF/HF)

Passive RFID

NFC

Cellular (GSM/UMTS/LTE)Positioning accuracy:3m~10m

Positioning accuracy:1m~5mPositioning accuracy:1m~3m

Positioning accuracy:1m~2m

Positioning accuracy:1m~3m

Positioning accuracy:0.01m~1m

Positioning accuracy: 0.1m~1m

Positioning accuracy: 0.1m~1m

Power consum

ption

Figure 4.1: Comparison of power, coverage, and data rate of tags implemented bydifferent short range wireless technologies.

considering the coverage range, accuracy and power consumption, the UWB tech-nology is the most power-efficient candidate for short-range (<10m) accurate posi-tioning. And the IEEE 802.15.4 compliant 2.4-GHz active RF is one of the mostcost-efficient technologies for long-range positioning implementations in the indus-trial environment.

However, as a trade-off, at the receiver side the ultra-short pulses and largebandwidth of the IR-UWB signal increase the complexity and power consumptionfor signal recovery. The high cost of the UWB receiver thus limits the massive ap-plication of the UWB-based positioning system, especially in the industry which issensitive to cost and power consumption. Although the large bandwidth is a burdenin the receiver design, the low-power emission spectrum also enables coexistence ofthe UWB signal with the other narrow-band technologies such as the 2.4-GHz RF,without interfering each other [135].

4.2 2.4-GHz/UWB Positioning Platform

The software and hardware architecture of the positioning platform is shown inFigure 4.2. The main contributions of the platform include five aspects: the designof an asymmetric system structure, hybrid tag, communication protocol, rang-ing/positioning algorithm, and SDR UWB reader network.

4.2. 2.4-GHZ/UWB POSITIONING PLATFORM 53

UserAccess

Drivers

Other drivers

Internet Other wireless Internet Database

storageSensor

repository

Graphic engine GUI

Control/protocol

Positioning algorithm Optimization

Security control

Operating system

Server

core

UWB interface

2.4-GHz interface

Internet interface

Other interface USB Power

controlI/O

Database storage

Flash

UWB interface

2.4-GHz interface

Power control Flash Sensors Other I/O

Schedule/control

Ranging/positioning

...

...

Schedule ...

MCU

MCUTag

Reader

Softw

are

Har

dwar

e

Figure 4.2: Hardware and software structure of the proposed positioning platform.


server

objects

...

clusterM clusterN

A coordinator &

multiple 2.4-GHz, UWB

readers

A coordinator &

multiple 2.4-GHz, UWB

readers

Tags with 2.4-GHz transceiver

and UWB transmitter

downlink uplinkcontrol

2.4-GHz

RF

position

2.4-GHz

RF/UWB

Figure 4.3: The hybrid technology based positioning system.

4.2.1 System Architecture

Based on the characteristics of the UWB technology, and the requirements of thepositioning in the industrial IoT, a 2.4-GHz RF and UWB hybrid locating systemwhich features asymmetric communication links, that is, optional 2.4-GHz RF orUWB uplink (from tag to reader), and 2.4-GHz RF downlink (from reader to tag),is proposed.

In the system, a designed hybrid tag which has both the 2.4-GHz transceiver andthe UWB transmitter is used. The 2.4-GHz RF technology is used by the readers totransmit commands to control and organize the tags. And UWB technology is notused in the downlink, not only relaxes the tags design and the power consumption,but also retains long control/operation coverage of the system.

Figure 4.3 illustrates the system. Considered the complex background and cov-erage problem in large-area in the industrial environment, the system is composedof multiple clusters. Each cluster is arranged to cover a specific area according todivisions, such as different floors and various functional workshop, and controlled byone central-controlled coordinator (CCR) and a group of reference readers (bothUWB readers and 2.4-GHz RF readers). According to positioning accuracy de-mands, there exists critical site and non-critical site in each cluster. The UWBbased positioning is employed at the critical site. The reference reader listens tothe data sent by the tags while the CCR sends commands and synchronizationinformation to the tags [136].


2.4-GHz antenna

6cm

Top Bottom UWB antenna

Battery ASIC UWB TX

CC2530

4cm

Debug ports

2.4-GHztransceiver

Memory

Powermanagement

MCU

UWBtranmitter

2.4-GHzInterface

UWBInterface

Figure 4.4: The UWB/2.4-GHz hybrid tag.

4.2.2 Hybrid tag

Figure 4.4 illustrates a prototype of the designed hybrid tag which contains botha 2.4-GHz transceiver and an ASIC UWB transmitter [115, 137]. In the tag’sstructure, a microprocessor is used to control both the 2.4-GHz RF/UWB basedtransmission, and the 2.4-GHz RF based reception. A UWB antenna and a 2.4-GHzRF antenna are connected to the 2.4-GHz transceiver and the UWB transmitter,respectively.

4.2.3 Communication Process

A communication process of the positioning in one cluster of the system is describedin Figure 4.5. Both frequency and time multiplexing are employed as shown. Specif-ically, each tag is assigned to a unique time slot and frequency channel to send eitherthrough a 2.4-GHz RF channel or through a UWB channel depending on the de-tecting area. To maximum improve energy efficiency, both the transmission andthe reception of the tags are working in a duty cycle manner, that is, not onlythe data transmissions but also the data receptions including order/commands and


synchronization information must obey to the schedules. The RF module of eachtag will not turn on until a pre-defined transmission or reception time is reached.

Server

CCR

. . .

Frame n

Listen

Command

S(Tag1)

S(Tag2)

S(Tag3)

S(Tag1)

S(Tag2)

S(Tag3)

Listen

Pos&F

S(Tag4)

Pos&F Pos.

Command

Frame n+1

Pos&F Pos Pos&F Pos

Listen

Command

S(Tag1)

S(Tag2)

S(Tag3)

Command

Frame n+2

Pos Pos&F Pos

S(Tag4)

Listen

Command

S(Tag4)

. . .

New Info. assigned

New Info assigned

ListenRef.

reader1

Ref. readerL

...

ListenS(Tag1)

S(Tag2)

S(Tag3)

S(Tag1)

S(Tag2)

S(Tag3)

Listen

S(Tag4)

S(Tag1)

S(Tag2)

S(Tag3)Listen

S(Tag4)

Listen

S(Tag4)

Sync.

Ch 1

Ch L

...

Listen Listen

Listen Listen Listen

. . .

Sync.

Sync.

Sync.

Sync.

Sync.

Figure 4.5: The communication process used in each cluster.

SleepActive

2.4-GHz Tx

Start

UWBTx

Initialization

Tx timer not reached

Tx timer reached

Tx in 2.4-GHz mode

Tx in UWBmode

Tx setup

TS end & Tx complete

TS or Tx not complete

TS or Tx not complete

Rx time reached


Rx timerreached

TS end & Tx complete Rx time not

reached


Rx timer not reached

TS or Rx not complete

TS end & Rx complete

Rx(2.4-GHz)

Figure 4.6: The state transition of the RF module of each hybrid tag.


Start

System Initialization:(CCR, 2.4-GHz & UWB readers, tags)

Data transmission by Tag (UWB/2.4-GHz, Channel_n)

Data reception(2.4-GHz & UWB Reader)

ToA/RSS detection by reader,Position calculation by server

Data transmission by Tag (2.4-GHz,Channel_m)

Data reception(2.4-GHz Reader)

RSS detection by reader,Position calculation by server

Yes Moving to normal site ?

Moving to critical site?

Time to Synchronize?

Time to Synchronize?

In critical site?

NoNo

Yes

Yes Yes

No No

Yes No

Tag Initialization/update(controlled by CCR): (TH, channel, update rate, etc.)

Tag Initialization/update (controlled by CCR): (TH, channel, update rate, etc.)

Yes Yes

Time to transmit? Time to transmit?

No No

Tag

“Sleep”

Tag

“Sleep”

Figure 4.7: The operation flowchart of the 2.4-GHz/UWB hybrid positioning.Adapted from Paper IV


The state transition of one hybrid tag is shown in Figure 4.6. And the op-eration flow of the positioning system including a switch between the 2.4-GHzRF based transmission manner and the UWB based transmission manner is de-scribed in Figure 4.7. As shown in Figure 4.6 and Figure 4.7, each tag keepsits RF module turned-off until its scheduled position update, that is Tx ,or com-mands/synchronization reception, that is Rx, time reached. Once its RF module isturned on and it is responsible for positioning update, it first detects if it is workingin a critical site where the UWB transmission mode should be selected. Then theposition update is sent by the corresponding UWB or 2.4-GHz transmitter. Thetransmitter would be turned off when the transmission is completed. Otherwise, ifthe RF module is activated for the reception, information of transmission modes orfrequency channels switch, new transmission time slot, and new reception sched-ule for synchronization or command may probably be received. In this case, thetag then re-configure these parameters and employ the new setups in the followingoperations.

4.2.4 State-of-the-art UWB Receiver

From the reader aspect, two kinds of receiver, that is, the 2.4-GHz RF receiver andthe UWB receiver, are needed. Compared with the 2.4-GHz narrow-band receiver,the UWB receiver design is more challenging due to its large bandwidth. Classifiedby whether full sampling is required, there are coherent and non-coherent UWBreceivers.

Coherent UWB Receiver

Figure 4.8 shows the classic correlator-based coherent UWB receiver architecture.The received signal is correlated with a local template signal by a mixer after filteredand amplified by an RF front-end. And the output of the mixer is directly sampledby an analog-to-digital converter (ADC) for baseband processing. It is not feasibleto realize such coherent receiver for the UWB signals because of the challenging ofnot only the high sampling rate but also the difficult selection of the local template,which is used as a matched filter to distinguish the UWB pulses, . This kind ofreceiver is also called as a Matched Filter receiver [138].

Non-coherent UWB Receiver

The non-coherent receiver used a simpler structure is an optimum selection com-pared with the conventional coherent structure. It is capable of processing theUWB signal at an affordable expense of power and cost based on an energy de-tector (ED) or an autocorrelation (AcR) receiver scheme. Figure 4.9 and Figure4.10 show the architectures of the ED receiver and the AcR receiver, respectively.In the non-coherent UWB receiver structure, an integration window is chosen to


RF front-end

Filter Amplifier

ADCUWBBack-end

Template

r(t)

s(t-τ )

Mixer

Figure 4.8: Architecture of the correlator-based (Matched filter) UWB receiver.

Mixer

RF front-end

Filter Amplifierr(t)

ʃ ADC

Square-law device

IntegratorUWBBack-endr(t)

Figure 4.9: Architecture of the energy detection (ED) based UWB receiver.

Integrator

RF front-end

Filter Amplifierr(t)

ʃ

Delay

r(t-τ )

ADCUWBBack-end

Figure 4.10: Architecture of the self-delay based (AcR) UWB receiver.

accumulate the energy of the received signal including all multi-path componentswithin the window period.

Unlike the coherent receiver, the ED receiver only exploits the envelope, thatis, instantaneous power, of the received signal by using the square-law device andits following energy integrator [139, 140]. In this case, no phase comparison isperformed, so that the phase-based modulation is useless. To maintain the phasecomparison and benefit from the phase information, the AcR receiver is preferred.The AcR receiver uses an analog delay line and a mixer to compare the receivedsignal. This processing is equivalent to an autocorrelation device which has a fixeddelay [141, 142].


4.2.5 The Proposed SDR UWB ReceiverTo achieve accurate positioning estimate, a ToA-based distance measurement isrequired at the UWB receiver for obtaining a fine time domain resolution of thereceived UWB signals. This makes the SDR UWB receiver a more feasible solution,because 1) it is power demanding and expensive to make the ADC work at leastat the Nyquist rate, that is, twice the signal bandwidth. And it is challengingto implement a conventional Rake receiver structure to capture enough amountof energy as the coherent receiver demands; 2) it is crucial to synchronize theUWB pulses at the scale of nanosecond duration without fine complex processingalgorithms or low clock jitter; 3) it is difficult to realize a nanosecond-level integratorusing the analog circuit to achieve centimeter-level distance estimation by the non-coherent UWB receiver.

ToA Estimator and Algorithm

By using the SDR receiver, it replaces the analog circuits by digital as much aspossible and realizes complex processing of the received UWB signal. The proposeddigital implementation of the UWB receiver for ranging/positioning, that is, a ToAestimator, is illustrated in Figure 4.11.

(.)2 ∑

ToA Estimator

Coarse search

max

UWB signal

square integration

compare ∑

Fine search

integration threshold

ADC(a)

(b)

(d)

(c) (e)

Figure 4.11: The block diagram of the proposed SDR-based ToA estimator.

The ToA estimator exploits the ED receiver structure. An ADC is used first toconvert the received signal r(t) to digital format r[n]. Then it collects the energyby squaring and accumulating it over a given time and frequency window Wi

zj [k] =i+Tint,c∑n=i

tnr2[n] (4.4)

where i denotes index of the sample of the kth integration window, Tint,c is thelength of the integration window used in the coarse search, ti is the start time ofthe integration window. n = 1, ..., N,N =

⌊Tf

tsp

⌋is the index of samples of signal in

one pulse repetition cycle Tf at sampling time tsp, and k = 1, ...,K,K =⌊

Tf

Tint,c

⌋represents the index of integration output. zj [k] is considered as the energy blockof the kth integration window of the jth pulse repetition interval.


The coarse search in the ToA estimator is aiming to rapid distinguish the pulseposition in each repetition interval out of the received signals. Thus, consideredthe multi-path components and the impact of the RF front-end, the integrationwindow length can be selected from several nanoseconds to milliseconds dependingon the data rate and the demanded searching speed. A maximum search is usedafter the integrator to find out the maximum energy block zj [k]max.

An index comparison between the maximum energy block zj [k]max and thesquared signal r2[n] is carried out to indicate the start point of of the location ofthe jth pulse, kmax,j , inside r2[n]. Then a fine search for ToA is employed forr2[n] in the distinguished area of pulse location. Similarly, a smaller integrationwindow Tint,f is used, and we can get a group of integration blocks z′j [k]. Unlikethe maximum search used in the coarse pulse location search, a threshold-basedleading edge [143, 144] search is used to estimate the ToA of the received signal asthe first energy block that exceeds the threshold η,

ktoa,j = first{k|z′j [k] > η} (4.5)

And the absolute ToA of the jth pulse of the received signal is estimated as

t̂toa,j = (Tint,c − 1)kmax,j + (Tint,f − 1)ktoa,j2 (4.6)

An instance illustration of the ToA estimator process corresponding to the pro-posed blocks shown in Figure 4.11 can be found in Figure 4.12.

0 500 1000 1500 2000 2500 3000 3500 4000Samples

Vol

tage

(a) UWB signal

0 500 1000 1500 2000 2500 3000 3500 4000Samples

Pow

er

(b) Signel after square-law

0 500 1000 1500 2000 2500 3000 3500 4000

max block

Samples

Energy

(c) Output of coarse search

0 500 1000 1500 2000 2500 3000 3500 4000 4500

j j+1

kmaxk

max

Samples

Energy

(d) Located pulses

0 50 100 150 200 250 300 350 400

ktoa, j

j

Samples

Energy

(e) Fine search of j

0 50 100 150 200 250 300 350 400

j+1

ktoa, j+1

Samples

Energy

(f) Fine search of j + 1

Figure 4.12: The ToA estimation process using the proposed ToA estimator.


SDR UWB Reader Network

An SDR UWB receiver for TDoA location estimation is built based on a Lecroyoscilloscope. The oscilloscope can perform up to 40-GHz sampling rate and supportreal-time built-in program for the ToA and TDoA calculation [145]. The block dia-gram of the SDR TDoA estimation based receiver network is shown in Figure 4.13.Four of the input channels of the oscilloscope is considered as four independentUWB receiver front-ends, and a four-channel ToA estimator based on the structureshown in Figure 4.11 is implemented by the built-in programmable software. Ab-solute ToA estimations achieved by the ToA estimator are exploited in the TDoApositioning program for location estimation after a calibration unit.

ToA Estimator

Calibration unit

(Signal alignment)

TDoA (Sychronization)

& Positioning

Filter LNA

Filter LNA

Filter LNA

Filter LNA

CH1

CH2

CH3

CH4

tToA1

tToA2

tToA3

tToA4

t’ToA1

t’ToA2

t’ToA3

t’ToA4

Oscilloscope

Figure 4.13: The structure of the SDR UWB reader network.

4.2.6 Implementation and ExperimentAs shown in Figure 4.14, implementation of the positioning platform for experi-mental setup consists of a computer (local server), a CCR (2.4-GHz RF transceiverwith 8051 core), a SDR UWB reader network (4 independent ToA estimator anda uniform TDoA positioning and processing back-end), two 2.4-GHz readers (workin different frequency channels), and three hybrid tags (one in critical site, and twoin non-critical site).

TDoA Positioning

In the experiment, only basic RSS distance estimation is used for the 2.4-GHz RFbased positioning. Hence, only the positioning results using the TDoA methodunder the communication context of the UWB signal are shown.

In Figure 4.15, a 3000-times statistical result of absolute ToA estimation ofone tag at a fixed location is drawn. This result can be described by a Gaussiandistribution with mean µ and variance σ2. The final ToA is computed according


ServerCable/Ethernet

2.4-

GH

z

EthernetCab

le

control

UW

B

data

data

2.4-

GH

z

Critical site Non-critical site

UWB reader network

2.4-GHz readers

2.4-GHz coordinator

Figure 4.14: The overview of the platform implementation.

to weighted algorithm after filtering out estimations with large errors,

ttoa =∑i∈[µ−ε,µ+ε] nit̂toa,i∑i∈[µ−ε,µ+ε] ni

(4.7)

where |ε| ∈ [σ, 2σ] is the bound of filter.

4.95 5 5.05 5.1 5.15 5.2

x 10−8

0

100

200

300

400

Time (s)

Num

ber

Figure 4.15: The absolute ToA estimation based on the received UWB signal.

Then by employing the TDoA method, the relative ToA measurement resultsusing one of the input channels as the reference channel can be obtained for location


estimations. The Newton estimation algorithm is used to compute the locationsaccording to Equation 4.2. An instance of the positioning results of 28 test locationsis shown in Figure 4.16.

0 1 2 3

0

1

2

3

distance (m)

dist

ance

(m

)estimatereference

Figure 4.16: A positioning example using TDoA estimation.

To analyze the positioning accuracy, the root-mean-square error (RMSE) isintroduced. A statistic of 1600 times position estimations of one test point isshown in Figure 4.17. It can be seen that over 75% of the location estimations canachieve less than 10 cm positioning accuracy, that is, 1220 out of 1600.

Energy Budget

Figure 4.18 shows a comparison of the estimated average power requested for bothdata transmission and commands/synchronization information reception of one tagby using a single 2.4-GHz RF technology and the 2.4-GHz RF and UWB [137]hybrid technologies. It draws the average power consumption as a function of theposition update rate where the rate of receiving commands sent by the CCR isfixed assumed as every hour, and the synchronization rate of the tags is 10 times oftheir position update rate in average. It can be seen by using the UWB to transmitdata, the hybrid tag can consume about 37.5% less energy compared with the oneusing the 2.4-GHz RF to transmit.


0 20 40 60 80 1000

100

200

300

400

500

600

700

RMSE (cm)

Num

ber

of te

sts

Figure 4.17: The RMSE distribution of the estimated locations of one test pointover 1600 times estimations

10−3 10−2 10−1 10010−4

10−3

10−2

10−1

100

Location upade rate (times/s)

Est

imat

ed a

vera

ge p

ower

of T

x an

d R

x (A

h)

Normal Tag(2.4−GHz for Tx and Rx)Hybrid Tag(UWB for Tx and 2.4−GHz for Rx)

Figure 4.18: Estimated average power consumption of Tx and Rx of each tag (2.4-GHz: 32 mA for Tx and 27 mA for Rx, the Tx period for position update is 5 ms,the Rx period for command is 5 ms, and Rx period for synchronization is 1 ms;UWB: 16 mA for Tx, the Tx period for position update is 1 ms).


4.3 Summary

In this chapter, a positioning platform based on the 2.4-GHz RF and UWB hy-brid techniques is illustrated. This platform is implemented based on the extensionof the architecture described in Chapter 3. That is, multiple RFID techniques,the UWB and the 2.4-GHz RF, are used in the communication to provide dif-ferent positioning accuracy. The designed RFID tag prototype which consists ofboth the UWB interface and the 2.4-GHz RF interface demonstrates the feasibilityof handling multiple RFID communication techniques in one RFID tag. And thecorresponding communication process and system architecture enable such commu-nications. An SDR UWB reader network is built based on an oscilloscope. Withthe help of the designed improved ToA/TDoA-based positioning algorithms, thepositioning platform can provide flexible positioning accuracy up to less than 10cm error. Furthermore, this platform structure also capacitates other techniquesand algorithms to be implemented depending on other application requirements.

Chapter 5

Conclusions and Future Work

5.1 Thesis Summary

This thesis describes an RFID communication and positioning system with high-reliability, low-latency, and accurate-positioning capabilities for the industrial IoTsystem.

As the development of the automation and Internet technologies, the 4th gener-ation of the industrial revolution which relies on the basis of the IoT is introduced.Among the three-layer architecture of the industrial IoT system, the performanceof data acquisition in the Object Layer dominates the whole network and service.Consequently, the appreciated system architecture, communication technology, andthe corresponding implementation protocols in the acquisition system of the ObjectLayer are discussed in Chapter 2. According to the specific working environment,the requirements of the acquisition system for the industrial applications are: de-terministic number of objects/functions under observation/operation process/taskpurpose, reliable communications among the objects and the network server withfailure resistance, data overload and recovery capabilities, latency-aware perfor-mance for real-time response, deployable structure/protocol to handle the diversitytasks in multiple industrial environments, and flexible adaptive ability to fulfill QoSdemands in one or multiple working scenarios.

Under the considerations of the requests and the features illustrated in Chapter2, a designed discrete-structure gateway based RFID system and a contention-freecommunication protocol are explored in Chapter 3. One discrete gateway is com-posed of a coordinator and a set of readers. On the basis of an extended star topol-ogy, multiple gateways are connected to a local server, and the RFID tags attachedto the objects are connected to the coordinator and the readers of each gatewayaccordingly. This system structure can benefit deployment for larger capacities andcoverage. It also supports flexible configuration of the number of readers inside onecoordinator’s coverage in various industrial environments. Additionally, an inde-pendent control link and data link is achieved by the separation of the coordinator

67

68 CHAPTER 5. CONCLUSIONS AND FUTURE WORK

and the readers in each gateway. It enables extra failure resistance and emergencyreport mechanism in the protocol as mentioned in the instance design for controlapplication in Chapter 3. The contention-free protocol, MF-TDMA, which usesboth time and frequency multiplexing method is specified for the discrete systemarchitecture. It employs scheduled communication for both data link and controllink to provide deterministic access. The capability of multiple communicationchannels/techniques offers larger system capacity then. And the dedicated controlchannel enables the system to work in a full duplex manner. In the protocol, a ba-sic optional ARQ mechanism is used to improved the communication reliability, anindependent/uniform synchronization and control method and the slot allocationoptimization algorithm are employed to reduce the transmission delay. From theinstance implementations of the designed protocol for energy-constraint, latency-constraint, and control-oriented industrial applications, the usages of the designedmethods shown above are introduced in the concrete ways.

A positioning platform design based on the designed RFID system architectureis introduced in Chapter 4. The 2.4-GHz RF and the UWB hybrid technologies areused in the platform to support flexible positioning accuracy from meter level tocentimeter level on demand of QoS. Besides the proposed asymmetric communica-tion structure, a prototype of hybrid RFID tag with both the 2.4-GHz RF interfaceand the UWB interface is designed. The RFID tag is able to send informationvia both the 2.4-GHz radio and the UWB radio. And it only receives data viathe 2.4-GHz radio, that is no UWB receiver supported on the tag, which relaxesthe pressure of power consumption at the tag side. From the reader side, to takeadvantage of the fine positioning resolution in the time domain of the UWB sig-nal while providing a flexible testbed for multiple positioning algorithms, an SDRUWB reader network is implemented based on an oscilloscope. It can perform bothToA test and TDoA positioning in real time with the help of the execution of theembedded third-party program. An improved ranging and positioning algorithmis realized for the received UWB signals, and it is implemented in the SDR UWBreader network. From the demonstrated experimental implementation, an aver-age of 10 cm positioning accuracy is achievable when using the UWB signal. Thepositioning platform is a practical implementation of the designed RFID systemwhich employs two techniques within one coordinator’s coverage. On this basis,more flexible system implementations for different industrial applications can beexpected under the designed system architecture and protocol.

5.2 Future Work

As the growing demands of automation, networking, and informatization, the sug-gested future works of the industrial IoT system are distributed mainly over thefollowing aspects:

• Hardware improvement

5.2. FUTURE WORK 69

From the tag side, to connect "everything" to the network requires the RFIDtag to be able to perfectly attached to the objects without affecting theirphysical property while keeping a reliable connection to them. Therefore, thehardware improvement of the tag includes: 1) an efficient power managementmodule which can support continuous long-time power for the RFID tag; 2)be able to implement the RFID tag using printing electronics technology onflexible types of substrate, such as paper and plastic, for special industries;3) reasonable tag design of RF antenna with omni-directional radiation capa-bility for different substrates.

• Standards and compatibility improvementThe diversity of industrial applications increases the difficulty of applyingone protocol in all systems. The protocol should be extremely flexible andadaptive for not only the RF communication but also the function employedeach specific application. Therefore, based on the proposed system structureand communication protocol, further simplification of the protocol, reductionof the implementation complexity, and improvement of the compatibility arethe main future effort.

• Security improvementBoth the system software and the network security are the indispensable issueresearch under the context of the industrial IoT. In the Object Layer, datagenerated from some special machines, tool, or operation process should notbe revealed to the whole network. Additionally, a local backup of some of theoperation-related data is needed for errors or statistic analysis. In future work,the security modules with specific algorithms are requested to be implementedfor the industrial IoT system.

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