master-optimization of egprs link adaptation
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optimization of Egprs Link AdaptationTRANSCRIPT
HELSINKI UNIVERSITY OF TECHNOLOGY Department of Electrical and Communications Engineering
Jussi Nervola
OPTIMIZATION OF EGPRS LINK
ADAPTATION
COMPANY CONFIDENTIAL VERSION
(Appendix D included)
Thesis submitted in partial fulfillment of the requirements for the degree of Master of
Science in Engineering in Espoo on 16.01.2007
Supervisor: Professor Riku Jäntti
Instructor: M.Sc. Petri Grönberg
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HELSINKI UNIVERSITY OF TECHNOLOGY Abstract of Master’s Thesis
Author: Jussi Nervola Name of the Thesis: Optimization of EGPRS Link Adaptation Date: 16.01.2007 Number of pages: 76
Department: Department of Electrical and Communications Engineering Professorship: Communications Laboratory
Supervisor: Professor Riku Jäntti Instructor: M.Sc. Petri Grönberg
Abstract: EDGE (Enhanced Data Rates for GSM Evolution) with packet based service EGPRS (Enhanced GPRS) offers packet data service for the users of GSM network. EDGE was introduced in Release’99 version of GSM standard and it improves the performance of the system to a new level. Wireless networks are working in very challenging environment. The quality of a connection can change from very good (with line of sight to the base station) to very poor in short time. The performance of the system has to be optimized for every radio condition. In EGPRS there are nine different modulation and coding schemes (MCS) that offer different amount of robustness for data transfer. The coding scheme that offers the best performance in the current situation from the user point of view should be used. This requires automatic adaptation to the different circumstances from the system. The automatic selection of the most suitable coding scheme is called link adaptation. This thesis concentrates on optimizing link adaptation for EGPRS. The target was to get the performance of EGPRS link adaptation to the optimum level. First the baseline measurements were made and the performance and improvement potential of the current system were analyzed. Then changes to the link adaptation were implemented according to the analyses. Various versions of link adaptation algorithm were created and tested to see which offered the best performance and if the changes were working as intended. After every new version the gap between the implemented and ideal link adaptation was closing. As a result of this thesis the performance of EGPRS link adaptation was improved nearly to the ideal level in almost every environment. The performance improvement with the final optimized link adaptation version was clearly seen in laboratory and live network. In laboratory the throughput performance was improved by +11% in average. Coverage for EGPRS service was improved by 1-6 dB depending on circumstances. In live network throughput improvement in downlink data transfer was +11% and in uplink data transfer +31%. Although the results with the optimized link adaptation were optimal in almost every environment, there was still some room left for improvements with certain mobile stations (MSs).
Keywords: EGPRS, EDGE, link adaptation, EGPRS performance, packet data
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TEKNILLINEN KORKEAKOULU Diplomityön tiivistelmä
Tekijä: Jussi Nervola Työn nimi: EGPRS linkkiadaptaation optimointi Päivämäärä: 16.01.2007 Sivumäärä: 76
Osasto: Sähkö- ja tietoliikennetekniikan osasto Professuuri: Tietoliikennelaboratorio
Työn valvoja: Professori Riku Jäntti Työn ohjaaja: DI Petri Grönberg
Tiivistelmä: EDGE (Enhanced Data Rates for GSM Evolution) yhdessä pakettipohjaisen EGPRS (Enhanced GPRS)-palvelun kanssa tarjoaa pakettidatapalvelua GSM-verkon käyttäjille. EDGE esiteltiin GSM standardin versiossa Release’99, ja se nosti järjestelmän suorituskyvyn uudelle tasolle. Langattomat verkot toimivat eritäin haasteellisissa olosuhteissa. Yhteyden laatu voi vaihdella erinomaisesta erittäin huonoon lyhyessä ajassa. Järjestelmän suorituskyky on optimoitava jokaiseen radio-olosuhteeseen sopivaksi. EGPRS:ssä on yhdeksän eri modulaatio ja koodausluokkaa, jotka tarjoavat datansiirrolle eri määrän robustisuutta. Käytettävä koodaus tulee valita joka tilanteessa niin, että käyttäjän kokema suorituskyky maksimoidaan. Tämä vaatii järjestelmältä automaattista mukautumista ympäröiviin olosuhteisiin. Tätä automaattista koodauksen valintaa kutsutaan linkkiadaptaatioksi. Tämä diplomityö keskittyy EGPRS:n linkkiadaptaation toiminnan optimoimiseen. Työn tavoitteena oli saada EGPRS:n linkkiadaptaation suorituskyky optimitasolle. Aluksi nykyisen järjestelmän suorituskyky mitattiin ja analysoitiin, jotta parannuspotentiaali voitiin selvittää. Analyysien perusteella linkkiadaptaatioon tehtiin muutoksia. Linkkiadaptaatiosta tehtiin useita versioita, ja kaikki eri versiot testattiin, jotta nähtiin, mikä tarjosi parhaan suorituskyvyn ja olivatko järjestelmään tehdyt muutokset oikean suuntaisia. Jokaisen version jälkeen ero toteutetun ja ideaalisen linkkiadaptaation suorituskyvyssä pieneni. Diplomityön tuloksena EGPRS:n linkkiadaptaation suorituskyky parani lähelle ideaalitasoa melkein kaikissa olosuhteissa. Suorituskyvyn parantuminen oli selkeästi nähtävissä sekä laboratorio-olosuhteissa että oikeassa verkossa. Laboratoriossa datan siirtonopeus parantui keskimäärin +11%. EGPRS palvelun kantama parani tilanteesta riippuen 1-6 dB. Oikeassa verkossa parannus datan siirtonopeudessa oli downlinkissä +11% ja uplinkissä +31%. Vaikka optimoidun linkkiadaptaation suorituskyky oli lähellä optimitasoa melkein kaikissa olosuhteissa, jäi suoristuskykyyn parannettavaa joidenkin puhelinmallien (Mobile Station) kanssa.
Avainsanat: EGPRS, EDGE, linkkiadaptaatio, EGPRS:n suorituskyky, pakettidata
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Contents
Contents .............................................................................................................................. 3 Preface ................................................................................................................................ 4 Glossary .............................................................................................................................. 5 1. Introduction................................................................................................................ 7 2. Global System for Mobile Communications (GSM) ................................................. 9
2.1. Network Switching Subsystem (NSS)............................................................. 10 2.2. Base Station Subsystem (BSS) ........................................................................ 10 2.3. Network Management Subsystem (NMS)....................................................... 11
3. General Packet Radio Service (GPRS) .................................................................... 12 3.1. Network Architecture ...................................................................................... 12 3.2. Protocol Architecture....................................................................................... 13 3.3. Mobile Stations................................................................................................ 15 3.4. Mobility Management ..................................................................................... 16
4. Enhanced Data Rates for GSM Evolution (EDGE) ................................................. 18 4.1. Enhancements to GPRS................................................................................... 18
5. Performance of EGPRS............................................................................................ 21 6. EGPRS Link Adaptation .......................................................................................... 24
6.1. Operation of Link Adaptation.......................................................................... 24 6.2. Incremental Redundancy ................................................................................. 26 6.3. Bit Error Probability as Channel Quality Criterion ......................................... 27 6.4. Link Adaptation Algorithm ............................................................................. 29
7. Test Scenarios for EGPRS Link Adaptation Measurements.................................... 31 7.1. Laboratory Test Scenarios ............................................................................... 32 7.2. Laboratory Measurement Configurations........................................................ 32 7.3. Live Test Scenarios ......................................................................................... 36 7.4. Test Cases for Laboratory and Live Network.................................................. 37 7.5. Earlier Measurements on Link Adaptation...................................................... 39
8. Measurement Results and Optimization of Link Adaptation................................... 41 8.1. Baseline Measurement Results........................................................................ 41
8.1.1. Measurements in Variable RX-level Scenario........................................ 42 8.1.2. Measurements in Variable C/I Scenario ................................................. 44 8.1.3. Improvement Potential of the Current Link Adaptation ......................... 48
8.2. Optimization of Link Adaptation .................................................................... 48 8.3. Measurement Results with Optimized Values................................................. 51
8.3.1. Measurements in Variable RX-level Scenario........................................ 52 8.3.2. Measurements in Variable C/I Scenario ................................................. 55 8.3.3. Measurements in Fading Scenario .......................................................... 57 8.3.4. Measurements in Live Network.............................................................. 59
9. Results of the Optimization...................................................................................... 66 9.1. Performance in Laboratory Environment ........................................................ 66
9.1.1. Downlink Performance ........................................................................... 66 9.1.2. Uplink Performance................................................................................ 68
9.2. Performance in Live Network ......................................................................... 68 9.3. Further Study Items and Future Improvement Potential ................................. 69
10. Conclusions.......................................................................................................... 70 11. References............................................................................................................ 71
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Preface
This thesis work has been carried out at Nokia Networks in BSS System Verification
team in Espoo, Finland.
I would like to thank the supervisor of this thesis, Professor Riku Jäntti, for his comments
and advices, my instructor Petri Grönberg for his excellent guidance during the thesis
work and my superior Jarmo Nissilä and my original instructor Veli-Pekka Ketonen for
their support. I want to thank also all members of BSS System Verification and BSC
System Testing teams for their support especially on test network configuration tasks.
Helsinki, January 16th, 2007
Jussi Nervola
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Glossary
3GPP 3rd Generation Partnership Project
8-PSK 8-Phase Shift Keying
ARQ Automatic Repeat Request
AuC Authentication Centre
BEP Bit Error Probability
BLER Block Error Rate
BSC Base Station Controller
BSS Base Station Subsystem
BTS Base Transceiver Station
C Carrier (power)
C/I Carrier-to-Interference Ratio
CS Circuit Switched
CS-1/2/3/4 Coding Scheme (GPRS)
DL Downlink
ECSD Enhanced Circuit Switched Data
EDGE Enhanced Data Rates for GSM Evolution
EGPRS Enhanced General Packet Radio Service
EIR Equipment Identity Register
ETSI European Telecommunications Standards Institute
FDD Frequency Division Duplex
FDMA Frequency Division Multiple Access
FEC Forward Error Correction
FTP File Transfer Protocol
GGSN Gateway GPRS Support Node
GMSK Gaussian Minimum Shift Keying
GPRS General Packet Radio Service
GSM Global System for Mobile Communications
HLR Home Location Register
HSCSD High Speed Circuit Switched Data
HTTP Hypertext Transfer Protocol
I Interference (power)
IP Internet Protocol
IR Incremental Redundancy
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LA Link Adaptation
LLC Logical Link Control
MAC Medium Access Control
MCS Modulation and Coding Scheme (EDGE)
ME Mobile Equipment
MS Mobile Station
MSC Mobile Switching Center
NMS Network Management Subsystem
NSS Network Switching Subsystem
PCU Packet Control Unit
PDP Packet Data Protocol
PDU Packet Data Unit
PS Packet Switched
RA Routing Area
Rel4 GSM Release 4
Rel99 GSM Release 99
RF Radio Frequency
RFLO RF Local Oscillator
RLC Radio Link Control
RTT Round Trip Time
RX-level Received Power Level
SAIC Single-Antenna Interference Cancellation
SGSN Serving GPRS Support Node
SIM Subscriber Identity Module
TBF Temporary Block Flow
TC Transcoder
TCP Transmission Control Protocol
TDMA Time Division Multiple Access
TSL Timeslot
TU Typical Urban (Fading model)
TX Transmitter
UL Uplink
VLR Visitor Location Register
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1. Introduction
GSM (Global System for Mobile Communications) is the most popular mobile
telecommunication standard in the world. The standardization work for GSM was
finalized in 1990. The original GSM network was designed for circuit switched traffic,
mainly for voice. As the demand for wireless packet based services was increasing, GSM
standard was developed further. The packet data capability was introduced by GPRS
(General Packet Radio Service) in the Release’97 version of GSM standard. More
advanced service EDGE (Enhanced Data Rates for GSM Evolution) with packet based
service EGPRS (Enhanced GPRS) was introduced in the Release’99 version of GSM
standard and it improved the performance of the system to a new level.
Packet based wireless networks are operating in far more demanding and changing
environment than wired networks. They have to use complex and sophisticated methods
to compensate the changes in radio environment. The quality of a connection can change
from very good (with line of sight to the base station) to very poor. The performance of
the system has to be optimized for every radio condition. When the quality of the
connection is good, there’s no need for heavy error correction and the user level
performance can be kept as high as possible. On the other hand, when the link quality is
poor, the error correction is the only way to get the user data through the network. In
EGPRS there are nine different modulation and coding schemes that offer different
amount of robustness for data transfer. The coding scheme that offers the best
performance in the current situation from the user point of view should be used. This
requires automatic adaptation to different circumstances from the system. The automatic
selection of the most suitable coding scheme is called link adaptation (LA).
This thesis concentrates on optimizing link adaptation for EGPRS. (Term optimization is
not used in this thesis in its mathematical meaning but referring to improving the
performance of the system.) First the current performance level of the system has to be
measured to find out the improvement potential. After that the optimized solutions for
link adaptation have to be created and implemented. When a new link adaptation version
is ready for testing, the performance of that version has to be measured to see if changes
done to LA were improving the performance enough. After the measurements, if there is
still potential for improvement, a new version of link adaptation is to be created and
tested.
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The target of this thesis is to get the performance of EGPRS link adaptation to the ideal
level. That would create real benefits for the users of EGPRS as the quality of service
would be improved. As the measurements are done with real network elements and not
just in simulations, the improvements should be fully realizable also in commercial
operators’ networks.
Chapters 2 – 4 provide brief introduction to GSM, GPRS and EDGE networks. Special
attention is paid to the issues that have effect on the functionality of link adaptation.
Chapter 5 discusses the performance of EGPRS service. Operation of EGPRS link
adaptation is explained thoroughly in Chapter 6. Chapter 7 describes the used test
scenarios and test cases for link adaptation measurements. Link adaptation optimization
work and measurement results with original LA and optimized LA are presented in
Chapter 8. The summary of measurement results is presented in Chapter 9. Finally
Chapter 10 concludes the thesis.
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2. Global System for Mobile Communications (GSM)
In this chapter the circuit switched GSM network is described. In the next chapter we will
go through the requirements for packet based services. Although this thesis concentrates
on Enhanced Data Rates for GSM Evolution (EDGE), it’s sensible to go through the
basics of circuit switched GSM and packet switched data services in GSM (GPRS) as
EDGE uses mostly the same infrastructure.
Global System for Mobile Communications (GSM) is a second generation digital cellular
network standard. It uses Time Division Multiple Access (TDMA), Frequency Division
Multiple Access (FDMA) and Frequency Division Duplex (FDD) techniques in its radio
interface [1]. The first GSM specifications were completed by European
Telecommunications Standards Institute (ETSI) in 1990. These specifications introduced
circuit switched service to the GSM network.
Figure 1: GSM network architecture
GSM network consists of three subsystems: Network Switching Subsystem (NSS), Base
Station Subsystem (BSS), and Network Management Subsystem (NMS). Mobile Stations
(MS) are needed to be able to use network services. MS is a combination of terminal
BTS MS BSC
HLR
AuC
EIR
PSTN
Base Station Subsystem Network Switching
Subsystem
Air A-bis A-ter
BTS
MSC/VLR TC
A
Network Management Subsystem
Database
servers
Workstations
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equipment or in other words Mobile Equipment (ME) and Subscriber Identity Module
(SIM). SIM holds data needed for the subscriber to use the network. The interfaces
between all these subsystems are open and therefore it’s possible to use equipment of
different vendors in every subsystem. GSM network architecture with circuit switched
service is presented in Figure 1.
2.1. Network Switching Subsystem (NSS)
Network Switching Subsystem is responsible for call control, charging and mobility
management in GSM network. The most important component in NSS is Mobile
Switching Center (MSC). It controls and routes all calls in the network. MSC has usually
also an integrated Visitor Location Register (VLR) where it stores information about the
subscribers in its service area. VLR has only a temporary database for the current users in
the area. Home Location Register (HLR) is used for storing subscribers’ data and location
permanently. The security to the GSM network is provided by Authentication Centre
(AuC) and Equipment Identity Register (EIR). AuC handles authentication and key
management of subscribers and EIR is a database that contains a list of all valid mobile
equipment in the network. AuC and EIR are usually implemented as a part of HLR.
2.2. Base Station Subsystem (BSS)
Base Station Subsystem is responsible for radio path control in GSM. It has three
components: Base Station Controller (BSC), Base Transceiver Station (BTS) and
Transcoder (TC). BSC is the central network element of the BSS and it controls the radio
network. Main functions of BSC are connection establishment between the MS and the
NSS, mobility management, statistical raw data collection and signaling support for A-
and Air-interfaces. BTS is a network component that handles the Air-interface taking care
of Air-interface signaling, ciphering and speech processing.
The third component of BSS, Transcoder, is used to transcode speech to right format for
the Air-interface and fixed networks. In the Air-interface speech is compressed to 13
kbit/s bit rate (Full rate) (or 5,6 kbit/s bit rate (Half rate)) from 64 kbit/s bit rate used in
PSTN.
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2.3. Network Management Subsystem (NMS)
The purpose of the Network Management Subsystem is to monitor various functions and
elements in the network. NMS is usually implemented using databases and workstations
that are connected to the network elements. The NMS has three main functions: fault
management, configuration management and performance management. The purpose of
fault management is to ensure correct operation of the network and create alarms if
something is not working properly in the network. Configuration management is used to
control the current and possible new configurations of the network. The plan for new
network configuration can be done beforehand and then later the planned changes can be
implemented quickly and easily. Performance management is used to collect performance
data from network. With this data the operator is able to see if the network meets its
planned performance levels and if there are differences between different areas in
performance.
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3. General Packet Radio Service (GPRS)
Circuit switched GSM offered also data service but the maximum data rates with CS data
were not high: 14,4 kbit/s. Also the circuit switched nature of the service was far from
ideal for bursty traffic. These were the main reasons why the standardization work began
for General Packet Radio Service (GPRS). GPRS offers packet switched based data
service for the users of GSM networks. Packet based networks offer better bandwidth
usage than circuit switched networks especially when the traffic is bursty like e.g. in web
browsing or receiving e-mails. GPRS has been in GSM standards since Release 97. It was
originally standardized by ETSI but now the standardization work has been handed over
onto the 3GPP.
The basic idea of GPRS is that the capacity that is not momentarily used by voice traffic
can be given to packet data users [1]. This helps to increase the average usage of
otherwise non-used radio resources (see Figure 2). As the GPRS data has lower priority
than voice, the voice users get service whenever they want despite of GPRS usage. Some
cells or timeslots can be dedicated only for GPRS use and so the packet service can be
offered also when all voice channels are reserved.
Figure 2: GPRS increases average network usage
3.1. Network Architecture
GPRS requires some new network elements to GSM network: Serving GPRS Support
Node (SGSN) and Gateway GPRS Support Node (GGSN). SGSN takes care of the
conversion between IP protocols and BSS protocols. It’s connected between BSC and
GGSN. SGSN also routes data to right GGSN, performs authentication, data compression
Time of day
Load
Voice traffic
Unused capacity
Load
Voice traffic
GPRS data traffic
Average usage level
Time of day
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and ciphering. SGSN has also interaction with MSC and HLR. Interaction with MSC is
possible only if optional Gs-interface is in use.
The task of GGSN is to route packets to other packet networks (as internet) and packets
to individual mobile stations. GGSN also allocates IP addresses to mobile stations. From
the external networks’ point of view GGSN is just a router to a sub network because it
hides the GPRS infrastructure from the external networks. The Architecture of GPRS
capable GSM network is presented in Figure 3.
Figure 3: Architecture of GPRS capable GSM network
3.2. Protocol Architecture
As GPRS support is added to the network, a new set of protocols is needed [2].
Interworking between the new network elements is done with these new protocols. The
protocols used between MS and BSS (where link adaptation is working) are the physical
and RLC/MAC layer. GPRS protocol architecture is presented in Figure 4.
Figure 4: GPRS Protocol architecture
BTS MS BSC+PCU HLR
AuC
EIR
PSTN
Base Station Subsystem Network Switching
Subsystem
Air A-bis A-ter
BTS
MSC/VLR TC
A
SGSN
Gb
GGSN
Internet
Gr
Gn
Gs
IP IP
LLC
SNDCP
LLC
SNDCP
Physical
layer
Physical
layer
Air
MS BTS
L1bis
Network
service
BSSGP
L1bis
Network
service
BSSGP
Gb
SGSN
GTP
TCP or
UDP
IP
L1
L2
GTP
TCP or
UDP
IP
L1
L2
Gn
GGSN
RLC/ MAC
Abis L1 Abis L1
Abis
BSC + PCU
RLC/ MAC
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Physical layer is divided in two parts: physical RF-layer and physical link layer. 3GPP
reference configuration of the transmission chain of the physical layer is presented in
Figure 5 [3]. Physical RF-layer performs the modulation of the signal based on the bits
received from physical link layer. The same GMSK-modulation which is used in circuit
switched GSM is used also in GPRS. As a physical resource the system uses a part of the
radio spectrum dedicated for GSM. The most used GSM frequency bands are 850 MHz-,
900 MHz-, 1800 MHz- and 1900 MHz-band (there are also other bands specified for
GSM in [3]). For example GSM-900 frequency band means in practice 890 – 960 MHz
frequency range, where 890 – 915 MHz range is reserved for uplink and 935 – 960 MHz
range for downlink (FDD). The frequency band is divided into 124 channels that are 200
kHz apart from each other (FDMA). On every channel there are eight TDMA timeslots.
The physical link layer provides service for information transfer over a physical channel
between MS and the network. Most important services of physical layer are: Forward
Error Correction (FEC), synchronization, monitoring radio link quality, power control
and battery saving procedures (e.g. discontinuous reception). Four coding schemes are
defined for the packet data traffic channel: CS-1 – CS-4. They all have different code
rates resulting different error correction and throughput capabilities.
Figure 5: 3GPP reference configuration of the transmission chain of the physical layer [3]
RLC/MAC-layer offers reliable radio link to the upper layers. MAC (Medium Access
Control) layer takes care of radio connection management by defining the procedures that
enable multiple MSs to share a common transmission medium. On top of RLC/MAC
there is Logical Link Control Layer (LLC). It offers secure and logical link between MS
and SGSN. RLC (Radio Link Control) layer takes care of segmentation and reassembly
of LLC Packet Data Units (PDU). RLC layer has two transfer modes: acknowledged
mode and unacknowledged mode. In acknowledged mode RLC provides reliable service
Convolutional
coding
Block
coding
Reordering
and
partitioning
Inter-
leaving
Burst
multiplexing
Burst
building
Differential
encoding Modulation Transmitter
Receiver
Antenna
Information bits
(receive)
Air
interface
Information bits
(transmit)
Cryptological
unit (not used in GPRS)
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by using selective retransmissions for erroneous blocks. In unacknowledged mode
erroneously received RLC blocks are not retransmitted.
RLC throughput performance with different coding schemes is presented in Table 1.
Maximum transfer bit rate per one timeslot (TSL) for GPRS data is 8,0 kbit/s for CS-1,
12,0 kbit/s for CS-2, 14,4 kbit/s for CS-3 and 20,0 kbit/s for CS-4. As the bit rate
increases, the robustness gets worse. Link adaptation algorithm decides which of the
codecs is the most suitable in the current situation i.e. which coding scheme offers the
highest throughput in the current radio conditions.
Table 1: GPRS Coding Schemes
Coding Data rate
Data rate per TSL
excl. RLC/MAC Data rate
Data rate / 4 TSLs
excl. RLC/MAC
scheme per TSL headers per 4 TSLs headers
CS-1 9.05 kbit/s 8 kbit/s 36.2 kbit/s 32.0 kbit/s
CS-2 13.4 kbit/s 12 kbit/s 53.6 kbit/s 48.0 kbit/s
CS-3 15.6 kbit/s 14.4 kbit/s 62.5 kbit/s 57.6 kbit/s
CS-4 21.4 kbit/s 20 kbit/s 85.6 kbit/s 80.0 kbit/s
3.3. Mobile Stations
GPRS requires support from both the network and mobile stations. On MS side there are
three classes for GPRS mobile stations: Class A, B and C. Class A mobiles can use
simultaneously both packet and circuit mode connections. Class B mobiles don’t support
simultaneous traffic but are able to automatically switch the operation mode between
packet and circuit mode. These mobiles can be at the same time attached to GPRS and
GSM services. Class C devices can be attached to either GPRS or GSM network. The
devices may only be capable of using just one of the services but if they can use both
GSM and GPRS service, the selection between the services is done manually. The most
mobile stations on the market today are Class B equipment.
Mobile stations can usually use several timeslots for downlink and uplink data transfer.
This was possible already in the circuit switched GSM with HSCSD (High Speed Circuit
Switched Data). In GPRS the multislot class of the MS determines the maximum number
of timeslots the MS is capable to use simultaneously [Appendix B]. This multislot
capability is defined separately for DL and UL but also a maximum number of all used
timeslots (UL+DL) is defined. Nowadays Multislot Class 10 mobiles are very common.
They can use at maximum 4 timeslots for downlink and 2 for uplink but only 5 timeslots
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in all. That gives 80 kbit/s maximum bit rate for downlink and 40 kbit/s for uplink. The
bit rates presented here are RLC-layer bit rates, the application bit rate is lower due to
protocol overhead. Theoretical maximum bit rate for GPRS is 160 kbit/s with eight
timeslots.
3.4. Mobility Management
Mobility management in cellular networks is an essential feature. It makes it possible to
use the network services in the whole network not just in the cell where MS attached to
the GPRS service. The mobility management of GPRS is very similar to the one of GSM.
One or more cells form a routing area (RA) which is served by one SGSN. One routing
area is a subset of one location area.
Tracking of the mobile in the network depends on the mobile’s mobility management
state. There are three different states in mobility management [2]: idle, standby and ready.
The idle state is used when the user is passive and not attached to the GPRS network. In
this state the MS is not reachable by the GPRS network. In order to change the state and
be able to use GPRS the MS has to perform a GPRS attach procedure. The standby state
is used when the user has ended an active phase. The subscriber is still attached to the
mobility management and the location of the MS is known by the network within the
accuracy of a routing area. If MS sends data, it moves to ready state. The ready state is
used when MS is transmitting or it has just been transmitting data to the network. In ready
state SGSN is able to send data to MS without paging because the location of the MS is
known within the accuracy of a cell. In a GPRS detach procedure the MS moves back to
idle state. The GPRS detach procedure can be initiated by the MS or by the network. The
state transitions are presented in Figure 6.
Figure 6: MS GPRS Mobility Management States
IDLE READY STANDBY
GPRS attach
GPRS detach PDU transmission
Ready timer expiry or
Force to STANDBY
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When the MS moves in the network, its location information has to be updated. MS
performs a cell update when it changes cell within a routing area in ready-state. When
changing the cell to a new routing area in ready- or in standby-state, MS performs a
routing area update. There are two types of RA updates: intra-SGSN and inter-SGSN RA
update. If the new routing area is managed by the same SGSN as the old one, an intra-
SGSN RA update is used. If the new RA is managed by different SGSN, an inter-SGSN
RA update is used. When MS stays a long time in the same cell, the network has to know
that the MS is still reachable. In this situation periodic routing area update is made.
The mobility management state of the mobile has an effect also on the performance and
latency of the service because the procedures needed for sending and receiving data are
different in different states.
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4. Enhanced Data Rates for GSM Evolution (EDGE)
Wireless data has become an important service of mobile networks and demand for more
bandwidth has been growing all the time. ETSI started standardization of a new data
service that would offer higher bitrates than GPRS and finalized it in 1999. The new
service was called Enhanced Data Rates for GSM Evolution (EDGE).
EDGE offers great improvement to GSM data services by enhancing the data rates per
timeslot for multislot High Speed Circuit Switched Data (HSCSD) and GPRS. These
enhancements are called ECSD (Enhanced Circuit Switched Data) and EGPRS
(Enhanced General Packet Radio Service). In ECSD the maximum data rate is 64 kbit/s
due to limitations on the A-interface [2]. The throughput per timeslot is tripled when
compared with normal CS data, though. The ECSD throughput is quite low when
comparing it with EGPRS. The theoretical maximum throughput with EGPRS and eight
timeslots is 473 kbit/s (59 kbit/s per timeslot). This thesis will only concentrate here on
EGPRS because it has been more popular technology among the manufacturers than
ECSD.
4.1. Enhancements to GPRS
The design principle of EGPRS was to minimize the changes on GPRS specifications [4].
That minimizes the required chances to the network and makes sure that EDGE operates
easily with basic circuit switched GSM and GPRS. The carrier symbol rate (270,833
ksymbols/s), carrier pulse shape, burst duration and spectrum mask are the same for GSM
and EDGE [2] [5]. This ensures that EDGE and GSM can be used simultaneously in the
same cell and frequency (channel) but in different timeslots. EGPRS is built on top of
GPRS and therefore it’s quite easy to implement it to GPRS networks. EGPRS has major
impact on RF and physical layer, Abis-interface and some impact on RLC/MAC
protocols but the changes to other layers and protocols are minor [2].
The physical- and RLC/MAC-layer modifications were made to be able to offer higher
throughput. There are several enhancements in EGPRS in comparison to GPRS [6]: 8-
phase shift keying (8-PSK) modulation, 9 modulation and coding schemes, EGPRS link
adaptation, incremental redundancy (IR) hybrid automatic repeat request (HARQ) and
improved RLC/MAC retransmissions.
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The main reason why EDGE is able to triple the throughput per timeslot (with good link
quality) is the change of modulation from Gaussian Minimum Shift Keying (GMSK) to
8-PSK. In GMSK modulation the symbols are represented by changing the phase by - π/2
or + π/2. Each symbol carries thus one bit. The direction of the phase change determines
if the bit is 0 or 1. In 8-PSK modulation the phase is shifted by -13/8 π, -9/8 π, -5/8 π, -1/8
π, +1/8 π, +5/8 π, +9/8 π or +13/8 π. This means that three bits are mapped onto one
symbol. That makes it possible to transmit three times as many bits as with GMSK (see
Figure 7).
Figure 7: 8-PSK constellation vs. GMSK constellation
As 8-PSK signal is able to transfer more data than GMSK signal, it also needs stronger
signal because of more challenging reception. In other words, if signal strength is low or
there’s much interference, GMSK codecs provide better throughput. Therefore, EDGE 8-
PSK modulation’s highest data rates can be achieved only with limited coverage when
compared to GMSK modulation.
There’s difference in maximum transmit power between modulations: GMSK-modulation
has 2-3 dB and 3-6 dB higher average power than 8-PSK modulation on downlink and
uplink direction, respectively. This is due to the fact that the EDGE transceiver has to
fulfill the same norms as normal GMSK-transceiver: the heat dissipation and transmit
spectrum have to be acceptable [5]. 8-PSK is also more challenging modulation than
GMSK from transceiver point of view: in contrast to GMSK, 8-PSK has varying
envelope and therefore the mean output power has to be lower than with GMSK to
achieve amplifier linearity.
EGPRS has nine different Modulation and Coding Schemes: MCS-1 – MCS-9. MCS-1 –
MCS-4 use GMSK as modulation and MCS-5 – MCS-9 use 8-PSK as modulation. The
different modulation and coding schemes are presented in Table 2 [7]. Link adaptation
Q
I
(1,1,0)
(1,0,0)
(1,0,1)
(0,0,1)
(0,0,0)
(0,1,0)
(1,1,1)
(0,1,1)
Q
I (1)
(0)
GMSK 8-PSK
1 bit/symbol 3 bits/symbol
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selects the best MCS for the current radio conditions. With good link quality MCS-9 is
used and with poor quality MCS-1 is used. The lower the modulation and coding scheme
is, the more robust it is. EDGE has also Incremental Redundancy (IR) to improve the
performance of link adaptation. IR is explained in Chapter 6.2. This thesis concentrates
on EGPRS link adaptation and it is discussed more thoroughly in Chapter 6.
Table 2: EGPRS modulation and coding schemes
Scheme Modulation Data rate Data rate Code Header Blocks per Family
per TSL per 4 TSLs rate code rate 20 ms
MCS-9 59.2 kbit/s 236.8 kbit/s 1.0 0.35 2 A
MCS-8 54.5 kbit/s 218 kbit/s 0.92 0.35 2 A
MCS-7 44.8 kbit/s 179.2 kbit/s 0.76 0.35 2 B
MCS-6 29.6 kbit/s 118.4 kbit/s 0.49 0.33 1 A
MCS-5
8-PSK
22.4 kbit/s 89.6 kbit/s 0.37 0.33 1 B
MCS-4 17.6 kbit/s 70.4 kbit/s 1.00 0.5 1 C
MCS-3 14.8 kbit/s 59.2 kbit/s 0.80 0.5 1 A
MCS-2 11.2 kbit/s 44.8 kbit/s 0.66 0.5 1 B
MCS-1
GMSK
8.8 kbit/s 35.2 kbit/s 0.53 0.5 1 C
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5. Performance of EGPRS
It’s an essential matter concerning this thesis to understand how the maximal
performance in packet based wireless networks (like EGPRS) can be reached. The overall
performance of wireless networks is highly affected by the performance of the Air-
interference: more than 60% of the latency is created there [8]. That is the reason why it’s
important that link adaptation works optimally.
The data rates presented in Table 2 are the maximum throughput values that can be
achieved on the RLC layer with continuous data transfer. These maximum throughput
values differ from the end-user throughput [9]. Figure 8 illustrates a case with TCP data
transfer. End-user throughput is only a part of the maximum throughput. Data link effects
and upper layer effects will reduce throughput available for the user. Data link effects are
the set of factors that depend on the network conditions such as interference, timeslot
multiplexing and RLC signaling. Upper layer effects are dependent on the transportation
and application protocols (e.g. TCP, HTTP and FTP) used by each service.
Figure 8: End-user performance with TCP data transfer
Continuous data transfer can be achieved only after certain initiation and transfer
procedures [10]. A sample of mobile originated data transfer procedures is presented in
Figure 9. When MS wants to send data, it first has to perform GPRS attach and activate
PDP context. Then packet channel request is needed to be able to start sending and
receiving data. Only during continuous data transfer the maximum throughput can be
achieved.
End-user throughput
TSL capacity
Data link throughput
Interference
Multiplexing
RLC signaling
Upper layer overheads
TCP establishment
TCP slow start
Cellular events & TCP
Application layer
Data link
effects
Upper-layer
effects
Maximum throughput
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Figure 9: Mobile-originated data transfer in GPRS/EGPRS [18]
During data transfer TCP with its congestion control has great effect on the end-to-end
performance. TCP was originally designed for wireline networks [11]. In mobile
environment this can cause some problems because of the different characteristics of
wireline and wireless networks. The biggest difference between wireline network and
wireless EGPRS network is the larger round trip time (RTT) in EGPRS networks. This
has effect on the behavior of the TCP congestion control.
The operation of TCP congestion control is illustrated in Figure 10. First the slow start
algorithm of the TCP slows down the data transfer at the beginning of the transmission
because the congestion status of the network is not yet known. If no packet losses occur,
the TCP congestion window size will be increased step by step towards the maximum
(defined at the beginning of TCP transfer). In wireless networks the slow start phase takes
much longer time than in wired networks because it takes more time for the TCP
transmitter to receive acknowledgement messages for the sent packets (because of big
RTT). In slow start phase the TCP window size can be increased only after previously
sent packets are acknowledged. If one of the packets is lost during data transfer, TCP
interprets it as network congestion and reduces sending rate drastically.
In wired networks it is mostly network congestion that causes packet losses. In wireless
networks also the packet losses caused by poor link quality are interpreted by TCP as
network congestion which causes unnecessary reduction of throughput. This problem
doesn’t exist in EGPRS as RLC (in ACK-mode) takes care of the retransmissions [12] but
the problem of data losses is translated into variable RTT (caused by varying number of
RLC retransmissions).
Packet channel request
Packet immediate assignment
Packet resource request (optional)
Packet resource assignment (optional)
Data transmission
ARQ, feedback, channel coding change command
Data transmission
MS Network
Arrival of
Layer 3
data
Attach procedure
Context activation, link
establishment
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TCP maintains a timeout timer for the sent packets. The length of this timer depends on
the RTT measured by the TCP transmitter. In cell changes or when the link quality
decreases dramatically, RTT is increased suddenly. This sudden increase can cause TCP
timeout [13] and then the TCP congestion window size is set to 1 MSS (Maximum
segment size) and the slow start phase is started again.
Figure 10: TCP congestion window
On top of TCP, that is, on the application layer for example HTTP or FTP can be used.
They both create overhead and require their own initiation procedure before continuous
data transfer can be achieved.
All these different characteristics of signaling, TCP, FTP and HTTP affect the end-user
performance as illustrated in Figure 8 and need to be taken into account when optimizing
the performance of the system. By understanding the protocol behavior it’s also possible
to estimate the maximum theoretical end-user performance in different scenarios.
Slow-start
threshold
Threshold
Linear increase
Exponential
increase
t
Window
size
Packet loss
Linear increase
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6. EGPRS Link Adaptation
The radio path in wireless communication systems is a challenging environment for
mobile equipment. It requires far more complex and sophisticated measures from
equipment than the wired networks. There are several phenomena that affect the quality
of radio path: attenuation, noise, interference and fading [14]. Attenuation and noise are
familiar phenomena also in wired networks but they are far more significant in wireless
networks than in wired ones. Interference and fading, on the other hand, are not very
common in wired networks. Interference to the radio signal is caused by other equipment
that are using the same frequency somewhere near enough. In GSM networks interference
is caused by base stations (BTS) and mobile stations (MS). Fading is a phenomenon that
is caused by the distortion that the signal experiences over certain propagation media. The
most common types for fading are fast fading and slow fading. Fast fading is known also
as multipath propagation fading. It results from the superposition of transmitted signals
that have traveled different paths to the receiver reflecting e.g. from buildings and
ground. Different paths cause different attenuation, delay and phase shift in every signal
component. Fast fading is caused by small movements of a mobile. Also scatterers around
a (stationary or moving) mobile cause fast fading. Slow fading, on the other hand, is large
scale fading that is caused by for example obstructions in propagation environment.
6.1. Operation of Link Adaptation
The task of link adaptation is to optimize the EGPRS performance with respect to the
quality of the radio path. Link adaptation works on the Air-interface, between MS and
BTS and is controlled by BSC. The link conditions on the Air-interface can change from
good receive quality with line of sight to the base station to very challenging conditions
far away from the base station with high interference. These changing conditions require
ability from the system to adapt to the current radio environment. In very good conditions
with high received power level (RX-level) and low interference there is not much need
for error correction and most of the available bits in the RLC block can be used for user
data. On the other hand, when the conditions are poor (low RX-level, high interference),
the system has to sacrifice many of the bits for error correction, and when the conditions
get poor enough, even the modulation has to be changed to be able to get the wanted data
through the network without errors. The task of the link adaptation is to maximize the
throughput in all different conditions.
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The way how link adaptation adapts to the current radio conditions is that it changes the
coding and modulation based on the link quality information reported by MS and BTS.
More robust codecs are selected when the link quality gets worse and less robust codecs
are selected when the quality gets better. When bit rate is high, the robustness to time
dispersion and MS’s speed is decreased because of small amount of error correction [5].
When more robust coding is needed, the user bit rate is decreased because the only way to
be able to receive the transferred data correctly is to increase the amount of redundancy.
This variability in coding is made possible (as stated earlier) by using nine different
modulation and coding schemes, all with different amount of error correction and two
modulations. The nine different modulation and coding schemes are MCS-1 – MCS-9.
MCS-1 is the most robust scheme and MCS-9 the least robust scheme (offering the
highest bit rate in good conditions). Figure 11 shows the performance of different MCSs.
LA algorithm has to choose the right MCS for different situations. The ideal link
adaptation would follow the envelope of throughput of different MCSs [15] selecting the
MCS with the highest throughput. In practice, the link adaptation chooses the MCS that
meets best the predefined criteria.
Figure 11: Performance of different MCSs from [4]
The Automatic repeat request (ARQ) procedure in EGPRS is based on selective
retransmission of erroneous packets [16]. If data blocks are not received correctly, they
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are retransmitted. In the retransmissions also the Incremental Redundancy (IR) is usually
used [2].
There are three families within MCSs: A, B and C. These determine the possible codecs
that can be used on retransmissions: the retransmission has to be performed with an MCS
that belongs to the same family with the MCS of the original transmission. MCS-9, MCS-
8, MCS-6 and MCS-3 belong to family A, MCS-7, MCS-5 and MCS-2 to family B and
MCS-4 and MCS-1 to family C. Within every family there is some similarity between the
payload sizes which makes it possible to resegment the block for retransmissions [17]. In
Nokia’s solution it is not possible to resegment the RLC blocks. This restricts the
retransmission to use the same modulation as in the original transmission. The MCS
choice in retransmission with and without re-segmentation is specified in [18]. The block
structure of different MCSs is presented in Figure 12.
Figure 12: Block structure of MCS-1 – 9
6.2. Incremental Redundancy
The Incremental Redundancy (IR) used in retransmissions improves EGPRS’s
performance compared to GPRS by introducing 0-3 dB gain to system performance [15].
IR improves the performance especially if LA is not working optimally or the link quality
measurements are not perfect [16].
MCS-7
MCS-1 22 MCS-2 28 MCS-3
37 MCS-4 44 MCS-5 56 MCS-6 74
56 56 MCS-8
68 68 MCS-9
74 74
redundancy from channel coding
RLC data block, number of bytes
RLC/MAC block (radio block)
11.2 kbps
14.8 kbps
17.6 kbps
8.8 kbps
22.4 kbps
29.6 kbps
44.8 kbps
54.4 kbps
59.6 kbps
GMSK
8-PSK
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IR is working by adjusting the code rate to actual channel conditions by incrementally
sending redundant data until the decoding is successful. In addition the receiver has to
store all the failed transmissions to be able to combine the different versions of the
transmission [19]. Figure 13 shows how the IR is working when MCS-9 is used. First the
data is convolutionally encoded with coding rate 1/3. Before the first transmission 2/3 of
the bits are punctured. That leads to basic code rate 1. It means that the same number of
bits is transmitted as was in the original data. While the retransmissions are done, the
code rate drops to 1/2 after the first retransmission and 1/3 after the second
retransmission. After the second retransmission we have three times as much bits as the
original transmitted data contained, so we have increased the redundant information. That
increases the probability to receive the bits correctly. To be able to operate, IR needs
successful reception of header information [4]. That is the reason why headers are coded
more robustly than data parts (see Table 2). If the header is not received properly, the IR
is unable to operate because the receiver doesn’t know to which packet the transmission
belongs.
Figure 13: IR transmission and combining with MCS-9
6.3. Bit Error Probability as Channel Quality
Criterion
Link adaptation needs link quality reports from MS and BTS to be able to adapt to the
changing conditions. In EGPRS the link quality is measured in terms of Bit Error
Probability (BEP) [20]. BEP expresses the probability of having a bit error and it is
determined based on the soft values from the receiver reception (soft values are the raw
bit values interpreted from the received symbols). The receiver (in BTS and MS)
original data
1/3 coded data
1st xmission
2nd xmission
3rd xmission
1st decoding attempt
2nd decoding attempt
3rd decoding attempt
r = 1/3
r = 1/2
r = 1/1
r = 1/1
r = 1/1
r = 1/1
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measures the BEP values on every TDMA burst and computes two measurement values,
namely mean BEP and CV_BEP (i.e. coefficient of variation of BEP), for each RLC
block (one block consists of four bursts) as follows:
∑=
=4
14
1_
i
iburstblockBEPBEPMEAN (1)
∑
∑ ∑
=
= =
−
=4
1
24
1
4
1
4
1
4
1
3
1
_
i
iburst
k i
iburstkburst
block
BEP
BEPBEP
BEPCV (2)
Where BEPburst i is the BEP of ith burst, MEAN_BEPblock is the mean BEP averaged over a
block, CV_BEPblock is the CV_BEP for a block, i is the number of burst in a block and k
is the number of burst in a block.
After this the mean BEP and CV_BEP values are averaged over a measurement period.
The duration of this period can vary from 1 block duration to 25 block durations. The
averaging is done to every timeslot and modulation type separately as shown below:
0R ,xeRe)(1R 1n1nn =⋅+⋅−= −− (3)
nblock,n
n1n
n
nn MEAN_BEP
R
xeNMEAN_BEP_T)
R
xe(1NMEAN_BEP_T ⋅⋅+⋅⋅−= − (4)
nblock,n
n1n
n
nn CV_BEP
R
xeCV_BEP_TN)
R
xe(1CV_BEP_TN ⋅⋅+⋅⋅−= − (5)
Where n is the iteration index, incremented per each radio block, MEAN_BEP_T Nn is
the average of mean BEP of one TSL during measurement period, CV_BEP_T Nn is the
average of CV_BEP of one TSL during measurement period, Rn denotes the reliability of
the filtered quality parameters, e is the forgetting factor (depending on measurement
period) and xn denotes the existence of quality parameters for the nth block (i.e. if the
radio block is intended for this MS; xn values 1 and 0 denote the existence and absence of
quality parameters, respectively).
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Finally the BEP-values are averaged over used timeslots for each modulation separately
as shown below:
∑
∑ ⋅
=
j
(j)
n
j
(j)
n
(j)
n
nR
NMEAN_BEP_TR
MEAN_BEP (6)
∑
∑ ⋅
=
j
(j)
n
j
(j)
n
(j)
n
nR
CV_BEP_TNR
CV_BEP (7)
Where MEAN_BEPn is the average of mean BEP during measurement period, CV_BEPn
is the average of CV_BEP during measurement period, n is the iteration index at
reporting time and j is the channel number.
These BEP measurements, namely MEAN_BEPn and CV_BEPn for GMSK modulation
and MEAN_BEPn and CV_BEPn for 8-PSK modulation, are used as an input for link
adaptation. In uplink data transfer the link adaptation receives these BEP measurements
from the BTS and in downlink data transfer these values are received from the MS in DL
ACK/NACK message.
6.4. Link Adaptation Algorithm
The BSC uses look-up tables in selecting the MCS based on BEP reports. The input
information used in the look-up tables are the MEAN_BEP and CV_BEP measurements
received from the receiver (MS or BTS). There are three different look-up tables:
Modulation selection table, 8-PSK MCS selection table and GMSK MCS selection table.
The link adaptation algorithm is presented in Figure 14. First the modulation type
decision is made between GMSK and 8-PSK. If the received BEP values indicate poor
link quality, GMSK-modulation should be used and if the BEP values indicate good
quality, 8-PSK-modulation should be used. When GMSK is chosen as modulation, the
MCS is selected from the GMSK MCS selection look-up table. When 8-PSK is chosen as
modulation, the MCS is chosen from the 8-PSK MCS selection table. This chosen MCS
is then used for data transmission until new BEP reports are received and link adaptation
algorithm is used again in deciding the new MCS. In Table 3 there’s an example of the
look-up table for 8-PSK MCS-selection from 3GPP specification [20].
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Figure 14: Link adaptation algorithm
Note that BEP measurements are needed for both modulations but if only one modulation
is used during a measurement period, only BEP-values for the used modulation are
received. In that situation we need to convert these values to other modulation’s BEP
values in order to use the look-up tables as described. So also look-up tables for
conversions from 8-PSK BEP values to GMSK BEP values and from GMSK BEP values
to 8-PSK BEP values are needed. During 8-PSK data transfer GMSK BEP-values are
usually received because RLC control blocks use always GMSK. The above-mentioned
conversion tables are needed especially when using GMSK modulation as no 8-PSK BEP
values are received during GMSK data transfer.
In the beginning of transmission the link quality and BEP-values are not known by the
BSC until the first measurement reports are received. Until then BSC is using predefined
MCS. This predefined MCS can be adjustable or fixed. The initial MCS affects quite
much to the performance of the network because the link adaptation is not working until
the first reports are received. If this MCS is too high, there are problems when the link
quality is poor. On the other hand if the initial MCS is too low, it reduces the performance
when the link quality is good.
Table 3: MCS selection table for 8-PSK from 3GPP specification [20]
8-PSK MEAN BEP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
1 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 8 8 8 8 8 8 9 9 9 9
2 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 8 8 8 8 8 8 9 9 9 9
3 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
4 5 5 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
5 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
6 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
7 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
8-PSK CV BEP
8 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9
Selection of
modulation
Selection of
GMSK MCS
Selection of
8-PSK MCS
GMSK chosen as modulation
8-PSK chosen
as modulation
Chosen MCS
(MCS-1 – 4)
Chosen MCS
(MCS-5 – 9) GMSK Mean BEP
8-PSK Mean BEP
GMSK CV BEP
8-PSK CV BEP
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7. Test Scenarios for EGPRS Link Adaptation
Measurements
To be able to optimize the performance of the current link adaptation some test
measurements have to be done to see what the current system’s potential for improvement
is. First the test scenarios and cases for verifying the performance of the current LA need
to be defined. The same tests will later be made with optimized solutions to verify the
possible improvement in performance.
When designing the test cases, the emphasis has been on the end-user perspective. In the
tests the performance experienced by the user is to be verified. If any problems are found,
some other more detailed measurements are needed to get deeper understanding of the
way the system works and to identify the root cause for the non-optimal behavior.
A laboratory network and a live GSM test network are in use for these EGPRS LA tests.
The radio conditions in the live network are of course more realistic than the radio
conditions in the laboratory network but in the laboratory it’s possible to make more
accurate and repeatable measurements. The laboratory conditions are more stable and that
makes it possible to see the effect of changes made to the system more reliably. The live
network can be used to test and verify the final changes made for LA. There it can be
seen if the real impact of the changes was the same as intended and the same as in the
laboratory. That is important because the changes to the system, if they are successful, are
aimed to be used in real operators’ live networks.
In all laboratory measurements Nokia MetroSite base station (BTS) and Nokia BSC2i
(BSC) were used. The measurements were done in 1800/1900 MHz band. Signal
generator, spectrum analyzer and Propsim fading simulator [21] were used to support the
laboratory measurements. Signal generator was used in the measurements as a source of
interfering signal. Spectrum analyzer was used to analyze the signal level and signal’s
spectrum. Fading simulator was used for simulating multipath propagation of the signal
on the Air-interface. The MSs used in the tests were mostly Multislot class 10 devices
(max. 4 downlink and max. 2 uplink timeslots used for EGPRS) [Appendix B]. Some
other class MSs were used in the final verification of new EGPRS LA. The MSs used in
the tests were Rel4 and Rel99 phones (Rel4 MS meeting the requirements of GSM
Standard version Release 4 and Rel99 MS meeting the requirements of GSM Standard
version Release 99). Frequency hopping was not used in the tests. The configuration of
the laboratory network is presented in Figure 16.
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Figure 16: Laboratory access network
7.1. Laboratory Test Scenarios
In the laboratory there are three different types of scenarios: variable RX-level, variable
Carrier-to-interference (C/I) and fading with variable RX-level. The variable RX-level
scenario represents coverage limited scenario as all interference is noise [15]. In that
scenario only the RX-level from the BTS and MS is attenuated. The RX-level range is -
50 dBm – -108 dBm. No additional interference is added to the signal.
The variable C/I scenario represents capacity limited scenario as interference is added to
the signal and noise is not the dominant component. In that scenario RX-level is set to
stable -70 dBm and interference is generated by GMSK modulated signal. The
interference is attenuated so that the C/I-ratio is between 0 dB and 35 dB.
In the fading scenario (with variable RX-level) 3GPP specified 6-tap propagation models
[22] TU3 (Typical urban 3 km/h) and TU50 (Typical urban 50 km/h) are created with
Propsim radio channel simulator. These models simulate the multipath propagation of the
signal (in other words fast fading) in the air interface. The models can be found in
[Appendix A]. These models are used to simulate the real network in the laboratory to see
if the behavior of the system with fading is the same as in variable RX-level and variable
C/I scenarios. If the behavior in the laboratory fading scenario was similar, it would
suggest that the changes made to LA should work also in real environment where
multipath propagation is common. Link adaptation itself is unable to react fast enough to
fast fading but Incremental Redundancy helps in these situations [23].
7.2. Laboratory Measurement Configurations
Variable RX-level scenario is a basic measurement scenario in mobile phone network
testing. It’s easy to implement as just the transmitting power of the BTS or the attenuation
on the Air-interface can be adjusted. In the laboratory, an attenuator on the Air-interface
MS BTS BSC SGSN GGSN Server
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was used. The MS was placed into a shielded enclosure to avoid uncontrolled interference
from other laboratory or public networks. Rel4 MS was connected to the BTS with a
cable whereas Rel99 MS was connected to the BTS via normal Air-interface (in the
shielded enclosure) with its own antenna. The different kinds of Air-interfaces were used
to get more information about the behavior of LA in the measurements: cable-Air-
interface was more stable than the normal Air-interface whereas the normal Air–interface
represented better the “real” situation than the cable-Air-interface. The shielded enclosure
was connected with a cable to BTS’s transceiver. In that cable there were two attenuators:
one with constant 30 dB attenuation and one with variable 0 – 110 dB attenuation. The
measured RX-level range was from -50 dBm to -108 dBm. In both uplink and downlink
measurements the RX-level is the MS received power level (not BTS RX-level for
uplink). The MS RX-level is different from the BTS RX-level but to be able to compare
the uplink and downlink results the MS received power is used also in the uplink. The
reason for difference between MS and BTS received power-levels is the higher transmit
power of the BTS [24]. When MS RX-level is used in both UL and DL measurements,
the radio conditions (i.e. the location of the MS in a cell) remains the same regardless of
the data transfer direction. Configurations for variable RX-level scenarios are presented
in Figures 17 and 18.
Figure 17: Configuration for variable RX-level scenario with Rel4 MS
Figure 18: Configuration for variable RX-level scenario with Rel99 MS
0…110 dB Shielded test enclosure
BTS
Attenuator
Adjust MS RX-level
30 dB
0…110 dB Shielded test enclosure
BTS Adjust MS RX-level
30 dB
Attenuator
Attenuator
Attenuator
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Measurements in variable C/I scenario are bit more complex to carry out than in variable
RX-level scenario but that scenario is a bit closer to the real situation in live networks
than variable RX-level scenario. In C/I scenario the carrier signal is interfered with
another signal. In the measurements for this thesis the interference signal was GMSK
modulated signal. The interference was added simultaneously only to either uplink or
downlink direction to be able to analyze UL and DL operation more precisely. The
interference was added to the direction where the most of the data was transferred. This
means that for uplink data transfer the interference was on the uplink frequency and for
the downlink data transfer the interference was on the downlink frequency. There was an
attenuator for the interferer so that it was possible to adjust the C/I (carrier power was
kept constant). The interference level was adjusted in the measurements according to the
GMSK-signal level although both 8-PSK and GMSK were used. This was done because
we wanted the absolute interference level to be the same for different modulations as in
the real network. Configurations for variable C/I scenarios are presented in Figures 19
and 20.
Figure 19: Configuration for variable C/I scenario, interference in downlink
Figure 20: Configuration for variable C/I scenario, interference in uplink
0…110 dB Shielded test enclosure
30 dB
BTS
Signal Generator
0…110 dB
I
C+I C
Adjust interference
Adjust MS RX-level
level Attenuator
Attenuator
Attenuator
C
I
C+I
0…110 dB Shielded test enclosure
30 dB
BTS
Signal Generator
Adjust MS RX-level
Adjust interference level
Attenuator
0…110 dB Attenuator
Attenuator
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Measurements in fading scenario were done to simulate the live network with fading.
Propsim radio channel simulator was used to simulate fading. The fading was applied
only to one channel (UL or DL) to be able to adjust the signal levels easily. The fading
simulator is quite sensitive with the input signal levels so they needed to be adjusted
properly. The simulator takes the signal (to be altered) and RF local oscillator (RFLO) as
inputs. A signal generator was used as RF local oscillator and RFLO signal was adjusted
with -500 MHz offset to the real frequency (as defined in Propsim user manual): in these
tests that is 1,9894 GHz– 0,5 GHz = 1,4894 GHz for DL and 1,9094 GHz– 0,5 GHz =
1,4094 GHz for UL. The RFLO signal power was +10 dBm and the input signal was in
range -15 dBm - +10 dBm. As an output the simulator gave the altered faded signal. Also
circulators and isolators were used in this configuration to prevent the receiver (in MS or
BTS) from getting a stronger non-faded signal from other direction’s path. One circulator
or isolator causes 3dB attenuation in desired direction and 20 dB attenuation in other
direction. When downlink fading measurement was made, the downlink channel was
passed through the simulator and a variable attenuator whereas the uplink channel was
going directly to the BTS. During DL measurement the uplink channel was all the time in
good condition. Without the circulators the MS could have received a strong signal on the
uplink path and the DL path with fading would have been meaningless. In the uplink
measurements the downlink channel was in good condition and fading was done to the
uplink channel. In Figures 21 and 22 setup configurations for downlink and uplink
measurements are shown with used signal levels and attenuations.
Figure 21: Configuration for DL fading scenario with variable RX-level
0…110 dB
40 dB
BTS
Signal Generator
DL DL
UL
Radio Channel
RFLO
RF IN RF OUT
1
3
2 1 2 1 2 3
1
2
10 dB 30 dB Shielded test enclosure
Adjust MS RX-level
Simulator
Attenuator
Attenuator Attenuator Attenuator
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Figure 22: Configuration for UL fading scenario with variable RX-level
7.3. Live Test Scenarios
The live tests were executed in Ruoholahti, Helsinki. There were two different scenarios
for live network tests: drive test scenario and stationary test scenario. In drive test
scenario the measurements were done while driving a route. The route on the drive test
was driven at normal traffic speed (under 40 km/h). Although the speeds in the tests were
not exactly the same as in the laboratory (3GPP-models TU3 and TU50), the drive tests
gave a good reference for the fading measurements that were done in laboratory network.
Figure 15 shows the route on a map.
The stationary tests were executed at three different locations: at RX-levels -80 dBm, -90
dBm and -100 dBm. Locations for the stationary tests and the used BTS are marked on
the map (in Figure 15) as well. The measurements were executed on the back lobe of the
BTS as it offered more variation in link quality in a smaller area than the main lobe of the
BTS.
The live measurements were done with Nemo Outdoor software and hardware [25]. This
application records all the events on the Air-interface. This makes it possible to analyze
different figures such as RX-level, C/I, used MCS and RLC throughput after the test
drive.
0…110 dB
40 dB
BTS
Signal Generator
UL
UL
DL
Radio Channel
RFLO
RF OUT RF IN
1
2
3 2 1 2 1 2
1
3
20 dB 30 dB
10 dB
Shielded test enclosure
Adjust BTS RX-level Simulator
Attenuator Attenuator
Attenuator Attenuator Attenuator
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Figure 15: Live test driving route
7.4. Test Cases for Laboratory and Live Network
The measurements were made with three different applications: FTP-data transfer, HTTP-
data transfer and Ping. All these test measurements were executed with all different
scenarios and for Rel99 MS and Rel4 MS separately. These tests were mainly done to see
the behavior of the current system and to have some baseline measurements to which the
performance of the optimized LA could be compared.
As we are interested in end-user performance, the quality of service from the end-user
perspective was measured at the application level. FTP is a key application to measure
end-to-end throughput performance [15] and HTTP is widely used in web surfing. This is
why FTP and HTTP transfer measurements were chosen for throughput measurements.
These both protocols are using TCP which is the dominant protocol used in wired
networks and is becoming common also in packet based wireless networks.
In laboratory FTP throughput measurement tests were done with three different file sizes:
5 kB, 100 kB and 2 MB (DL) / 1 MB (UL). The files were non-compressible (e.g. zip-
files) so that the network elements handling the file were not able to improve the
performance by compressing the file. The measurement results were averaged over 3 – 5
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measurements. FTP data transfer cases were measured with a laptop. HTTP download
tests were done with 100 kB-html-page with 16 objects. The HTTP download for the
whole 100 kB-html page was measured with Microsoft Internet Explorer 6 [26].
4s HTTP download test was executed by downloading a html-page over HTTP and
measuring the amount of data that is received during the first four seconds of the data
transfer. The results were averaged over ten measurements.
Round trip time (RTT) is a key element when evaluating end-user performance. The
latency in the network affects directly to the quality of service: setup delay, TCP and
other upper layer protocols’ performance and service interactivity [9]. The RTT
measurements were done as active and idle. In both measurements the MS had performed
GPRS attach and PDP context activation before the RTT measurements. Active RTT
measurements mean that the MS sends ping-packets so often that new TBF (Temporary
Block Flow) doesn’t have to be created during different ping-packets. In idle RTT
measurements the time between the ping-packets is so long that TBF has to be created for
every packet separately.
RTT was measured with Ping application as an average over 100 samples with three
different packet sizes: 32 bytes, 256 bytes and 1460 bytes. The smallest packet gives a
good estimate for the minimum respond time whereas the biggest packet shows the
latency of a big packet. The RTT was measured between MS and gateway of the local
area network using Microsoft Windows XP’s built-in version of ping.
The summary of all test cases measured in the laboratory is presented in Table 4. All
these tests were done before and after the optimization.
Table 4: Laboratory test case summary
Laboratory Measurements
FTP-throughput measurements
HTTP-transfer measurements RTT measurements
5 kB 4 sec 32 Bytes
100 kB DL
100 kB 256 Bytes
DL
2 MB
Ping size:
1460 Bytes
5 kB
100 kB
UL
1 MB
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In the live test network we concentrated as well on throughput and RTT tests. These both
tests were done as stationary tests and driving tests. In the stationary locations the
measurements were made with 3 different RX-levels: -80 dBm, -90 dBm and -100 dBm.
The driving tests were executed by driving a route which has variable RX- and
interference levels. The summary of all test cases measured in live network is presented
in Table 5.
Table 5: Live network test case summary
Live Network Measurements
FTP-throughput measurements
HTTP-transfer measurements RTT measurements
DL 2MB 4 sec 32 Bytes
UL 1 MB DL
100 kB 256 Bytes
Ping size:
1460 Bytes
Also other tests were needed to find out in what conditions the system is not working
optimally and what could cause this non-optimal behavior. To see how the ideal LA
should work the measurements with fixed MCSs were executed with variable RX-level
and variable C/I scenarios. The BEP values were also measured as a function of C/I
because LA algorithm uses BEP measurements when deciding the MCS. By measuring
the BEP values with different C/I values it is possible to find relation between BEP and
the best suitable MCS. That should be a way to optimize the look-up tables.
7.5. Earlier Measurements on Link Adaptation
There are already quite many measurements made at Nokia about the performance of
EGPRS link adaptation. These earlier measurements offer quite a good benchmark
database to our tests and results. The potential for EGPRS LA performance improvement
was actually seen in these earlier made tests.
The reason why the current EGPRS LA is not working optimally (i.e. it’s not choosing
most suitable MCSs) in all situations seems to be, according to these earlier tests, that LA
uses too high MCSs. This doesn’t cause problems when the link quality is good but when
it gets worse, the throughput starts to deteriorate more than it should. If lower codecs
were used, the performance would be better in poor radio conditions. It is believed that
there’s possibility and potential to improve the current system performance. As said
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already in the introduction, the main goal for this thesis is to develop the EGPRS link
adaptation so that its performance would be closer to the optimal performance. The
performance of the LA should be improved with all applications (e.g. FTP-throughput,
Ping-RTT) especially when the link conditions are poor (low RX-level, low C/I). The
measurements with fixed MCSs, i.e. when EGPRS LA is disabled, offer a good reference
performance level. The performance of the system when link adaptation is used should be
as good as the best MCS’s performance at certain link quality level. It means that if at a
certain level MCS-3 offers the best throughput, also the link adaptation should use that
MCS.
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8. Measurement Results and Optimization of Link
Adaptation
The measurements for optimizing the EGPRS link adaptation were executed in the
laboratory and in the live network. First the baseline measurements were done in the
laboratory and with the help of these measurements some changes to the system were
made and various different test software builds were created. After these changes, the
performance with the new software versions was measured and the best one was chosen
for further tests. The chosen version was then compared to the original EGPRS link
adaptation algorithm. Although the number of measured samples in the measurements
was quite low, the results should present quite well the real performance of the system.
Reliability of the measurement results is analyzed in [Appendix C].
The performance with most suitable MCSs (i.e. MCSs that offer highest throughput in
current situation) represents the performance level of optimal or ideal link adaptation.
This performance level is later in this thesis referred as optimal performance level. The
link adaptation that offers this optimal performance level is referred as optimal LA.
8.1. Baseline Measurement Results
The baseline measurements were executed according to the test plan in three different
laboratory scenarios: in variable RX-level scenario, in variable C/I scenario and in fading
scenario (with variable RX-level).
In this chapter we will go through the measurements results for the variable RX-level
scenario and variable C/I scenario concerning the data throughput and round trip time
(RTT). In these measurements the performance of the link adaptation algorithm is
compared with the performance of all MCS-codecs. The tests were done by first
measuring the performance with link adaptation enabled and then the performance of
every MCS was measured separately. This way we are able to see what is the optimal
performance level and whether the current link adaptation algorithm is able to reach it. In
the end of this chapter a summary of improvement potential of the current system is
presented. The measurement values for throughput and RTT measurements in this thesis
are presented relative to reference values for confidentiality reasons. In throughput
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measurements the highest throughput value measured in the given scenario is used as a
reference level . Respectively, in RTT measurements the smallest RTT value measured in
the given scenario is used as reference level.
8.1.1. Measurements in Variable RX-level Scenario
In the variable RX-level scenario the RX-level was varied from -108 dBm to -50 dBm
and the end-user throughput was measured for each RX-level with FTP application. The
measurements were made separately for downlink and uplink direction (measurement
configuration is described in Chapter 7.2). The throughput was first measured with the
current LA algorithm and then without it using fixed MCSs. When link adaptation was
enabled, MCS-3 was used as an initial MCS in all tests.
The downlink throughput results obtained with the link adaptation algorithm and the
respective results with fixed MCSs in variable RX-level scenario have been plotted in
Figure 23. First we should analyze the difference in performance of the different MCSs.
In general it can be seen that throughput increases when the RX-level (i.e. the link
quality) increases. MCSs with high number (as e.g. MCS-9) offer better end-to-end
throughput than the MCSs with small number (as e.g. MCS-1) when the link quality is
good. When the link quality is poor, the situation is the opposite. The throughput of all
MCSs saturates when the RX-level increases high enough. The smaller the MCS number
is the smaller is the RX-level where the throughput saturates.
In downlink in the variable RX-level scenario the biggest performance difference
between the best fixed MCS and link adaptation is when the RX-level is below -100
dBm. The LA-algorithm seems to be unable to change to GMSK codecs (MCS-1 – MCS-
4) on these RX-level values. When the radio conditions get worse, FTP downlink
throughput deteriorates already when the RX-level is -102 dBm with LA. With fixed
GMSK codecs the FTP data transfer is possible down to -106 dBm. There is also some
room for improvement when the RX-level is reasonably high at -88 dBm – -90 dBm.
With these RX-level values the LA algorithm used MCS-9 even if the performance of the
MCS-8 was better than the performance with MCS-9.
The uplink throughput results obtained with the link adaptation algorithm and the
respective results with fixed MCSs in variable RX-level scenario have been plotted in
Figure 24. In the uplink the same kind of behavior can be seen as in the downlink
measurements. The LA is not using GMSK codecs even when the RX-level is below -95
dBm. With GMSK codecs the FTP data transfer was possible down to -106 dBm whereas
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with 8-PSK it was possible only down to -100 dBm. The throughput difference between
the best fixed MCS and link adaptation is bigger than the respective difference observed
in the downlink measurements and the reason for this is the power backoff of the 8-PSK
modulation (compared to GMSK modulation) [27]. When the link quality is good, the
link adaptation algorithm is working optimally and choosing most suitable MCSs.
Figure 23: Downlink FTP throughput in variable RX-level scenario
Figure 24: Uplink FTP throughput in variable RX-level scenario
UL FTP Throughput, variable RX-Level, 2 TSL
0.00
0.20
0.40
0.60
0.80
1.00
1.20
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
FTP Throughput (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to
GMSK modulation
DL FTP Throughput, variable RX-Level, 4 TSLs
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
FTP Throughput (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA uses MCS-9 although MCS-8
would offer higher throughput LA is unable to change to
GMSK modulation
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RTT in variable RX-level scenario was measured for the same RX-levels for which the
throughput was measured in this scenario. The measurement was done as active RTT
measurement and the size of the ping packet was 32 bytes.
The RTT results with the link adaptation algorithm and the respective results with fixed
MCSs in variable RX-level scenario are presented in Figure 25. The behavior of link
adaptation in RTT measurements is similar to the one seen in the throughput
measurements: when the link quality is good, link adaptation works well but when the
quality gets worse, LA is unable to change to GMSK codecs. The performance of link
adaptation is worse than the performance of the best fixed MCS when the RX-level is
below -95 dBm. With GMSK codecs the RTT times are still reasonable when the RX-
level of the link is as low as -106 dBm.
Figure 25: RTT with 32-byte-sized ping packet in variable RX-level scenario
8.1.2. Measurements in Variable C/I Scenario
The same tests that were done in variable RX-level scenario were done also in variable
C/I scenario. In the variable C/I scenario the C/I was varied from 0 dB to 35 dB. The
measurements were made separately for downlink and uplink direction (measurement
configuration described is in Chapter 7.2).
32B RTT, variable RX-Level
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
RTT (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to
GMSK modulation
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In downlink in variable C/I scenario the LA was in some circumstances able to change to
GMSK codecs unlike in variable RX-level scenario. That made it possible to reach the
optimum performance level also when the link quality was very poor (C/I under 5 dB).
However, at the point where the modulation should have been changed, the throughput
deteriorated completely (C/I was around 6 dB). Also the same behavior, link adaptation
using MCS-9 when MCS-8 would have offered better throughput, was seen here as in
variable RX-level scenario. This happened with good link quality (at C/I values 18 – 25
dB). The downlink throughput measurement results in variable C/I scenario are presented
in Figure 26.
Figure 26: Downlink FTP throughput in variable C/I scenario
The uplink performance of link adaptation in variable C/I scenario had exactly the same
problems as LA in the variable RX-level scenario: when the C/I is under 10 dB, the
performance of the link adaptation is below the optimum level. The uplink FTP data
transfer results in variable C/I scenario are presented in Figure 27.
DL FTP Throughput, C/I, 4 TSLs
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
0 5 10 15 20 25 30 35
C/I (dB)
FTP Throughput (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to GMSK
modulation early enough LA uses MCS-9 although MCS-8
would offer higher throughput
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Figure 27: Uplink FTP throughput in variable C/I scenario
RTT in variable C/I scenario was measured with the same C/I-ratios with which the
throughput was measured in this scenario. The measurement was done as active RTT
measurement and the size of the ping packet was 32 bytes.
The RTT measurement results in variable C/I scenario in downlink are presented in
Figure 28 and RTT measurement results in variable C/I scenario in uplink are presented
in Figure 29. The RTT measurements provided similar results as the RTT measurements
in the variable RX-level scenario. When the C/I is under 10 dB, the link adaptation is not
working optimally: GMSK is hardly used.
UL FTP Throughput, C/I, 2 TSL
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
0 5 10 15 20 25 30 35
C/I (dB)
FTP Throughput (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to
GMSK modulation
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Figure 28: RTT with 32-byte-sized ping packet in variable C/I scenario, interference in downlink
Figure 29: RTT with 32-byte-sized ping packet in variable C/I scenario, interference in uplink
32B RTT, C/I in DL
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
0 5 10 15 20 25 30 35
C/I (dB)
RTT (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to GMSK
modulation early enough
32B RTT, C/I in UL
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
0 5 10 15 20 25 30 35
C/I (dB)
RTT (relative)
MCS=1
MCS=2
MCS=3
MCS=4
MCS=5
MCS=6
MCS=7
MCS=8
MCS=9
LA on
LA is unable to change to
GMSK modulation
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8.1.3. Improvement Potential of the Current Link
Adaptation
The biggest opportunity to improve the current link adaptation algorithm is to optimize
the selection of MCS when the link quality is poor. The link adaptation algorithm is
unable to choose GMSK codecs even if the link quality is not good enough for 8-PSK
codecs. The situation when this behavior causes problems is when RX-level is below -
100 dBm or when C/I is under 10 dB.
There are also some other points where the performance of link adaptation can be
improved, especially in downlink: with reasonably good link quality, at RX-level -88 – -
90 dBm or at C/I values 18 – 25 dB the link adaptation uses MCS-9 although MCS-8
would offer better performance. This behavior is not severe: it just reduces the
performance slightly in the above-mentioned conditions. Nevertheless, it’s sensible to try
to optimize the performance in these conditions as well.
8.2. Optimization of Link Adaptation
Optimization of link adaptation was done by adjusting the modulation selection, MCS
selection and 8-PSK<->GMSK conversion look-up tables. Especially the modulation
selection table needed some modifications because the current link adaptation was often
unable to change to GMSK modulation even if the link quality was poor. Also some
minor modifications were done to the 8-PSK MCS selection table and GMSK MCS
selection table. All the modifications were done in order to optimize data throughput.
A number of BSC software test packets were created as candidates for the optimized link
adaptation algorithm. These different packages were tested to see which of the test
packets offered the best performance improvement compared to the original link
adaptation implementation. The different test packets were done with different approach:
some were more conservative, changing to lower MCSs earlier than the original LA
(when the link quality gets worse) and some tried to find the optimal performance level
with only small changes to the system. This kind of approach with many different test
packets was needed because at that point we knew that the changes were needed but we
were not able to say how big the changes had to be. After some measurements with the
test packets we were able to say which approach was the best for maximizing the
performance of link adaptation.
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In the first LA software test packets the modulation change to GMSK was tried to be
made earlier (when the link quality decreases) than with the original LA by modifying the
values in the modulation selection table. The most conservative LA version (the 1st
version of the optimized LA, referred later in this thesis as Optimized LA1) offered the
best performance but the behavior of that link adaptation version was not, however,
optimal. The improvement in performance was minor although significant modifications
were made to the modulation table.
The downlink performance of Optimized LA1 with variable C/I scenario is presented in
Figure 30 and compared to the performance of the original link adaptation. In the
downlink data transfer the throughput performance of Optimized LA1 was better than the
throughput performance of the original LA but nevertheless the optimized version was
not able to change to GMSK modulation at the right moment. The throughput was
deteriorated to zero when C/I was 9 dB. Then when the link quality got worse, the
Optimized LA1 was able to change to GMSK and the data transfer continued properly.
The uplink performance of Optimized LA1 with variable C/I scenario is presented in
Figure 31 and compared to the performance of the original LA. In the uplink data transfer
the difference in performance between the Optimized LA1 and the original LA was
minor. The throughput with optimized LA was only slightly better in low C/I-values (C/I
< 10 dB) than the throughput with the original LA. The gap to the optimal level
(performance of most suitable MCS) was still rather large.
Figure 30. Downlink throughput performance of optimized link adaptation version 1
DL Throughput, C/I, 4 TSLs
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25 30 35
C/I (dB)
Thro
ughput (r
ela
tive)
Original LA
Optimized LA1
Optimal LA
LA is unable to change to GMSK
modulation early enough
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Figure 31. Uplink throughput performance of optimized link adaptation version 1
When investigating why the modifications of the modulation selection table were not
improving the performance as intended, it was discovered that also the GMSK<->8PSK-
conversion table needed to be modified so that the values of the conversion table would
correspond to the values of the modulation selection table. Since the values didn’t
correspond to each other with the Optimized LA1, the modulation was not always
changed to GMSK early enough. In addition, it was realized that near the modulation
change point GMSK and 8-PSK were used alternately even though the radio conditions
didn’t change. When GMSK modulation was used and the BEP estimates for 8-PSK were
unrealistic high (as with Optimized LA1), the modulation was changed to 8-PSK (blue
arrows in Figure 32, left side). When 8-PSK was in use and GMSK BEP values were
measured, the modulation was changed back to GMSK (because no conversion table was
needed). This led to so-called “ping-pong”-effect and the usage of 8-PSK modulation at
the circumstances where it should not have been used, ruined the performance. Figure 32
illustrates this behavior (optimized modulation selection table and non-optimized
conversion tables).
UL Throughput, C/I, 2 TSL
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25 30 35
C/I (dB)
Thro
ughput (r
ela
tive)
Original LA
Optimized LA1
Optimal LA
LA is unable to change to GMSK
modulation
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Figure 32. Modulation selection and GMSK/8-PSK BEP values with optimized modulation
selection table and non-optimized/optimized conversion table
New link adaptation versions were then created with modified conversion table values.
The new values for the conversion table were defined by measuring the GMSK BEP and
8-PSK BEP values in the laboratory conditions with variable RX-level and variable C/I
(configurations are explained in Chapter 7.2). It was also checked that the values of the
conversion table were corresponding to the values of modulation selection table to avoid
any “ping-pong”-effects as seen in Figure 32.
Now with the modified GMSK<->8-PSK conversion table the performance and behavior
of link adaptation was as it was intended (in Figure 32; optimized modulation and
conversion tables). The results of the measurements with final optimized link adaptation
are presented in the next chapter.
8.3. Measurement Results with Optimized Values
The measurement results with final optimized link adaptation are reviewed in this chapter
and compared to the baseline results. The measurements were executed using the same
configurations as with the baseline measurements. Only the link adaptation was changed
to the best optimized version (the 11th version of optimized LA, referred later in this
thesis as Optimized LA11).
Several MSs were used in these tests because different MSs have different radio
performance. That obviously affects the behavior of link adaptation. Especially a MS
feature called SAIC (Single-antenna interference cancellation) has noticeable influence
on performance. SAIC is a 3GPP specified feature that is able to cancel the impact of
GMSK BEP
8-PSK BEP
C/I, RX-level
BEP
8-PSK used GMSK
used
Desired change of
modulation
Change of modulation in practice
due to unrealistic conversion table
Measured BEP value:
8-PSK or GMSK BEP
GMSK BEP-> 8-PSK BEP
conversions
GMSK and 8-PSK used alternately
GMSK BEP
8-PSK BEP
C/I, RX-level
BEP
8-PSK used GMSK
used
Change of
modulation
Measured BEP value:
8-PSK or GMSK BEP
GMSK BEP-> 8-PSK BEP
conversions
Optimized modulation selection
and conversion tables Optimized modulation selection table
and non-optimized conversion tables
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interference at the receiver. The cancellation works only for GMSK-modulation [28] and
that may cause problems for LA as GMSK quality is improved but 8-PSK quality isn’t.
The experience from the measurements was completely opposite, however: SAIC MSs
performed better with the optimized LA than non-SAIC ones.
Performance comparison of the link adaptation throughput measurement results is done
by calculating an integral (i.e the area under throughput measurement graph) over the
measured range for both original and optimized LA versions. Performance improvement
on used range is then calculated by comparing the results of the integrals. In variable RX-
level and fading scenarios the range where link adaptation performance is compared is
between RX-levels -110 – -75 dBm. In variable C/I scenario the comparison range is
between C/I-values 0 – 30 dB.
8.3.1. Measurements in Variable RX-level Scenario
In downlink throughput measurements in the variable RX-level scenario the optimized
link adaptation performed better than the original LA but with some older MSs (e.g.
Nokia 7270) the change of modulation from 8-PSK to GMSK was not optimal. This
caused 2 dB wide area where throughput deteriorated completely, around RX-level -102
dBm. This behavior was not seen with newer MSs (e.g. Nokia 6280). With new MSs
downlink performance of the link adaptation was close to the optimal performance level
with average improvement of +7% in whole range (-110 dBm – -75 dBm). The respective
performance improvement with older MSs was around +5%. Actually when link
adaptation was enabled the throughput performance in certain areas (RX-level -97 dBm –
-95 dBm) was even better than with the best fixed MCS. Downlink coverage for EGPRS
service was improved by 4 dB. Downlink throughput performance of the optimized link
adaptation in variable RX-level scenario is presented in Figure 33.
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DL Throughput, variable RX-Level, 4 TSLs
0%
20%
40%
60%
80%
100%
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
Throughput (relative)
Original LA
Optimized LA11 6280
Optimized LA11 7270
Optimal LA
Figure 33. Downlink FTP throughput in variable RX-level scenario
In uplink throughput measurements in variable RX-level scenario the optimized link
adaptation was working at optimal level with all MSs. Like in DL measurements in
certain area (around RX-level -88 dBm) the optimized LA was performing better than the
best fixed MCS. Performance improvement to the original link adaptation is clear:
average improvement of +17 % in whole range. Uplink coverage for EGPRS service was
improved by 5 dB. Uplink throughput performance of the optimized link adaptation in
variable RX-level scenario is presented in Figure 34.
UL Throughput, variable RX-Level, 2 TSL
0%
20%
40%
60%
80%
100%
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
Throughput (relative)
Original LA
Optimized LA11
Optimal LA
Figure 34. Uplink FTP throughput in variable RX-level scenario
RTT performance was also improved with the optimized link adaptation. Figure 35
presents the RTT measurement results made by using Ping packet size of 256 bytes in the
variable RX-level scenario. The improvement in performance was noticeable, though the
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performance was not on the optimum level. Behavior of RTT with 32 byte- and 1460
byte-sized Ping packets was quite similar to 256 byte-sized one. There were some
differences in performance between MSs. The MS used in Figure 35 is Nokia 6280.
256B RTT, variable RX-level
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-level (dBm)
RTT (relative)
Original LA
Optimized LA11
Figure 35. RTT with 256-byte-sized ping packet in variable RX-level scenario with Nokia 6280
Also in HTTP download measurements with 100 kB-html-page in variable RX-level
scenario there is clear performance improvement with the optimized link adaptation. As
with the original link adaptation web-page download time was ca. 60 seconds at -95 dBm
RX-level, the optimized link adaptation was able to perform the download even at RX-
level -102 dBm in ca. 35 seconds. HTTP download durations in variable RX-level
scenario with 100 kB-html page are presented in Figure 36.
100kB HTTP DL, variable RX-level
0.0
10.0
20.0
30.0
40.0
50.0
60.0
-70-75-80-85-90-95-100-102-104
RX-level (dBm)
Tim
e (s)
Original LA
Optimized LA11
Figure 36. HTTP download measurements with 100 kB-html-page in variable RX-level scenario
with Nokia 6280
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8.3.2. Measurements in Variable C/I Scenario
In downlink measurements in variable C/I scenario the performance of the optimized link
adaptation was quite similar to the performance in variable RX-level scenario. Also in
variable C/I scenario there are differences in downlink performance among different
phones. New MSs achieved close to optimum performance level whereas older MSs
didn’t behave optimally when the modulation was changed. With variable C/I scenario
and with optimized link adaptation the area where DL throughput deteriorated completely
was 1 dB wide, at C/I-levels 9 – 10 dB, for older MSs. The respective area with the
original LA was much wider, 4-5 dB. The performance improvement of the optimized
link adaptation is +15 % for downlink with new MSs. The respective performance
improvement with older MSs was +13%. Downlink throughput performance of the
optimized link adaptation with variable C/I scenario is presented in Figure 37.
DL Throughput, C/I, 4 TSLs
0%
20%
40%
60%
80%
100%
0 5 10 15 20 25 30 35
C/I (dB)
Throughput (relative)
Original LA
Optimized LA11 6280
Optimized LA11 7270
Optimal LA
Figure 37. Downlink throughput performance with variable interference (in DL)
In uplink measurements in variable C/I scenario the performance improvement of the
optimized link adaptation is not as big as the respective improvement in variable RX-
level scenario. This is due to the fact that the change of modulation is done earlier than
necessary when link quality decreases. Therefore the performance of optimized LA is
below the performance of the original LA between C/I-ratios 10 – 15 dBm. The behavior
of the optimized LA is very stable (data throughput continues down to C/I value of 0 dB)
when compared to the original link adaptation. Performance improvement in uplink is
+3%. Uplink throughput performance of the optimized link adaptation with variable C/I
scenario is presented in Figure 38.
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UL Throughput, C/I, 2 TSL
0%
20%
40%
60%
80%
100%
0 5 10 15 20 25 30 35
C/I (dB)
Thro
ughput (relative)
Original LA
Optimized LA11
Optimal LA
Figure 38. Uplink throughput performance with variable interference (in UL)
RTT performance of the optimized link adaptation is at the optimal level throughout the
whole range. There are some differences in performance depending on the used MS but
generally the performance improvement is bigger in variable C/I scenario than in the
variable RX-level scenario. RTTs with all different Ping packet sizes (32B, 256B, 1460B)
behave in the same way. RTT performance of the optimized link adaptation with 256
byte-sized Ping packet in variable C/I scenario is presented in Figure 39.
256B RTT, C/I in DL
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
0 5 10 15 20 25
C/I (dB)
RTT (relative)
Original LA
Optimized LA11
Figure 39. RTT with 256-byte-sized ping packet in variable C/I scenario (interference in
downlink) with Nokia 6280
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HTTP download measurements with 100 kB-html page also show a clear improvement
when the performance of the optimized link adaptation is compared with the performance
of the original LA in the variable C/I scenario. As with the original link adaptation it is
not possible to download the web-page when C/I is lower than 8 dB, the optimized link
adaptation enables downloads down to C/I = 0 dB in ca. 25 seconds time. HTTP
download durations in variable C/I scenario with 100 kB-html page are presented in
Figure 40.
100kB HTTP DL, C/I
0.0
10.0
20.0
30.0
40.0
50.0
60.0
3020151310986420
C/I (dB)
Tim
e (s)
Original LA
Optimized LA11
Figure 40. 100 kB-html page download performance over HTTP in variable C/I scenario
(interference in downlink) with Nokia 6280
8.3.3. Measurements in Fading Scenario
Based on the measurements made in downlink fading scenario the optimized link
adaptation is working very near the optimum level. The 1-2 dB wide areas (where
throughput deteriorated completely) that could be seen with older MSs on static
laboratory measurements were not seen in the fading scenario. As the signal quality is not
static, the quality is not poor all the time and the forward error correction and IR
procedures of EGPRS are able to provide some throughput for the user even if the radio
conditions are rather poor in average. Therefore the end-to-end throughput does not
deteriorate totally as happened in more static radio conditions.
In TU3 environment the downlink performance of the optimized LA is at the optimal
level almost throughout the range. On the point where modulation is changed the
performance of the optimized LA is 5% lower than the optimum level. With TU3 fading
the performance improvement on downlink with respect to the original link adaptation is
+4 % and coverage for EGPRS service is improved by 2 dB. Downlink throughput
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performance of the optimized link adaptation with TU3 fading scenario is presented in
Figure 41.
DL Throughput, TU3 Fading. 4 TSLs
0%
20%
40%
60%
80%
100%
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
Thro
ughput (relative)
Original LA
Optimized LA11
Optimal LA
Figure 41. Downlink throughput performance with TU3 fading and variable RX-level
In TU50 environment the downlink throughput performance is improved at low RX-
levels when comparing to the original link adaptation. With high RX-levels (RX > -85)
the performance is slightly reduced compared to the original LA. This is probably due to
the more conservative selection of codecs. This really pays off with low RX-levels where
performance is improved. With TU50 fading performance improvement with respect to
the original LA is +2% and coverage for EGPRS service is improved by 6 dB. Downlink
throughput performance of the optimized link adaptation with TU50 fading scenario is
presented in Figure 42.
DL Throughput, TU50 Fading, 4 TSLs
0%
20%
40%
60%
80%
100%
-110 -105 -100 -95 -90 -85 -80 -75 -70
RX-Level (dBm)
Thro
ughput (relative)
Original LA
Optimized LA11
Optimal LA
Figure 42. Downlink throughput performance with TU50 fading and variable RX-level
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8.3.4. Measurements in Live Network
Measurements in live network were executed in Ruoholahti as explained in Chapter 7.3.
The defined route was driven four times for downlink data transfer measurements and
two times for uplink data transfer measurements with the original and the optimized link
adaptation. RX-levels on the route were between -65 and -105 dBm, average RX-level
being -80 dBm. Average C/I was 25 dB. The BTS used in the live network was Nokia
UltraSite in 1800-MHz band. In Figure 43 there’s a summary of application level
throughput averages for both downlink and uplink. The optimized link adaptation
improved the performance for both directions: there was +11% improvement achieved in
the downlink throughput and +31% improvement achieved in the uplink throughput.
Scaling of the results was done using maximum downlink throughput level in laboratory
as a reference level.
FTP Throughput average in live-network during driving test
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FTP 2 MB DL FTP 1 MB UL
Throughput (relative)
Original LA
Optimized LA11
Figure 43. FTP average throughput during driving tests
On the entire route the optimized link adaptation seemed to be working more stable than
the original LA which resulted in higher overall downlink throughput. Figures 44 and 45
show downlink throughput performance along the driven route. A map with the route is
presented in Figure 15. The biggest difference between the original and the optimized LA
was on the western part of the route where RX-level was between -85 and -105 dBm.
There the optimized LA was much more stable and therefore was able to offer better
throughput than the original LA. Throughput measurement was made by downloading a 2
MB file using FTP application. As the download of the file was complete, the same file
was downloaded once again. This caused some breaks in transfer when one download had
ended and the next one was to be started. These breaks can be seen in Figures 44 and 45
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as individual black lines on the spots where the throughput on the other rounds has been
on a high level.
Figure 44. Downlink throughput during driving test with the original link adaptation
Figure 45. Downlink throughput during driving test with the optimized link adaptation
Figure 46 presents a more detailed view on the western part of the route by showing
retransmission rate along the route. The retransmission rate with the optimized LA has
decreased when comparing it with the retransmission rate that was observed with the
original LA. This is caused by more conservative selection of coding schemes. Since the
retransmission rate is lower, it seems that the optimized solution is choosing more robust
codecs than the original LA when link quality is poor.
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Figure 46. Number of retransmissions during DL data transfer at low RX-levels
If we want to see a more detailed view on the behavior of link adaptation, we have to
compare throughput performance at certain places on the route. Figure 47 shows RLC
throughput in downlink on the western part of the route (same part as in Figure 46). All
RLC throughput comparisons in this thesis are taken exactly from the same parts of the
route for both original and optimized solutions to see the changes in link adaptation
behavior reliably. In the western part the optimized link adaptation was working more
stable than the original LA as link quality got worse. No such drops in RLC throughput
were seen as observed with the original link adaptation. Also when link quality started to
get better, the optimized solution was able to continue data transfer much earlier than the
original one.
Figure 47. RLC downlink throughput (on Y-axis) as a function of time (on X-axis) at low RX-
levels (same part of the route as in Figure 45)
Original link adaptation
Optimized link adaptation
RX-level
RX-level
Original link adaptation Optimized link adaptation
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Figure 48 shows the downlink throughput performance on the southern part of the route.
RX-levels on this part of the route are between -70 dBm and -88 dBm. With these RX-
levels the original link adaptation used too much MCS-9 and this caused drops in
throughput. As the optimized link adaptation switched earlier to MCS-8 from MCS-9
when the RX-level got lower, the throughput was better than with the original LA. The
big wide drops in Figure 48 were caused by breaks between downloaded files.
Figure 48. RLC downlink throughput (on Y-axis) as a function of time (on X-axis) during southern
part of the route
On uplink data transfer the improvement in performance of the optimized link adaptation
can be seen even more clearly than in downlink. Figures 49 and 50 show uplink
throughput performance along the route. The route is exactly the same as in downlink
measurements. As RX-level on the MS side is -70 – -105 dBm, the RX-level on BTS side
is lower due to the smaller transmit power of the MS. This means that uplink conditions
in the same environment are more challenging than downlink conditions. That is the
reason for bigger performance improvement (+35%) than in downlink measurements
(+11%). Throughput with the optimized link adaptation was better than the throughput
with the original LA almost everywhere on the route. Especially on the western and
southern loops of the route the improvement was significant.
RX-level
RX-level
Original link adaptation
Optimized link adaptation
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Figure 49. Uplink throughput during driving test with the original link adaptation
Figure 50. Uplink throughput during driving test with the optimized link adaptation
If we analyze uplink throughput on certain parts of the route, the same improvement can
be seen in more detailed way. Figure 51 shows uplink RLC throughput on the same part
of the route as shown in Figure 47 (western part). Performance of the optimized link
adaptation was better than the performance of the original LA all the time. The optimized
version was able to continue data transfer throughout the challenging part of the route
whereas throughput with the original LA stalled several times.
Improved performance on uplink data transfer is due to the same reason as in downlink:
more conservative selection of MCSs. This can be seen in Figure 52 where the used
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MCSs are shown for the same part of the route as shown in Figure 51. With optimized
solution the usage of GMSK codecs was higher and the selection of the MCSs was more
stable than with the original LA. With the original LA big changes in MCS selection were
more common (e.g. MCS6->MCS3).
Figure 51. RLC uplink throughput (on Y-axis) as a function of time (on X-axis) during low RX-
levels (same part of the route as in fig. 46)
Figure 52. Used MCS (on Y-axis) as a function of time (on X-axis) in UL during low RX-levels
(as in fig. 50)
RX-level
RX-level
Optimized link adaptation
Original link adaptation
Original link adaptation
Optimized link adaptation
RX-level
RX-level
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Uplink throughput with a reasonably good link quality is also improved greatly with the
optimized link adaptation. Figure 53 shows uplink throughput performance on the
southern part of the route. The optimized LA was using mainly MCS-7 and MCS-8 on
that part of the route. The original LA was using in addition to MCS-7 and MCS-8, also
MCS-9. That had negative impact on uplink performance as MCS-9 was not robust
enough to successfully continue data transfer. This caused serious drops to throughput.
Figure 53. RLC uplink throughput (on Y-axis) as a function of time (on X-axis) during southern
part of the route
RX-level
RX-level
Original link adaptation
Optimized link adaptation
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9. Results of the Optimization
In this chapter the results of the link adaptation optimization are summarized.
Performance of the optimized solution is analyzed separately for tests in laboratory
environments and live network. Reason for this is that with laboratory measurements we
are able to see the behavior of the optimized LA in more detail and we can analyze better
the performance compared to the optimal level. Measurements in live network, on the
other hand, are needed to verify that the gain seen in laboratory measurements is also
visible in real radio environment.
Measurements done with the optimized link adaptation offered encouraging results. The
optimized LA was improving performance when compared to the original LA in all cases.
The performance was very near or at the optimum level with the optimized version
almost in all cases. Still there are some situations where the performance of the optimized
LA could be improved. Summary of performance improvements with the optimized link
adaptation is presented in Table 6.
Table 6. Summary of performance improvement with the optimized link adaptation
Laboratory measurements
Throughput improvement
Coverage improvement
Throughput improvement
Coverage improvement
RX-level DL +7% +4 dB UL +17% +5 dB
C/I DL +15% +1 dB UL +3% +6 dB
Live Measurements
Throughput improvement
Coverage improvement
Throughput improvement
Coverage improvement
drive route DL +11% <not
measured> UL +31% <not
measured>
9.1. Performance in Laboratory Environment
9.1.1. Downlink Performance
In laboratory conditions downlink throughput performance with the optimized link
adaptation was improved in average by +12 % in the whole range of the cell. The
improvement in RTT and html-page download measurements was also very clear.
Coverage where EGPRS data transfer can be used was improved by +4 dB. Performance
of the optimized link adaptation was near the optimum level almost in all cases with and
without fading.
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In laboratory measurements several MSs from different generations were used. This was
very helpful as different MSs had different receiver capabilities and that had effect also
on the behavior of link adaptation. New MSs were working at optimal level in all cases
with the optimized LA in downlink direction. With some older MSs there were still some
problems after the optimization when changing modulation. This caused 1-2 dB wide area
where throughput deteriorated completely. In that area, GMSK-modulation should have
been selected instead of 8-PSK-modulation. This behavior was seen in static
measurements in variable RX-level and variable C/I scenarios. In the measurements made
in fading scenario also these MSs were working optimally with the optimized LA.
The reason why certain MSs were not able to perform the change of modulation early
enough might be due to their receiver characteristic: their estimation for GMSK link
quality might be unrealistic. It was seen in the tests that the link quality with GMSK was
still at maximum level even if 8-PSK link quality was already so poor that no data could
be transferred with 8-PSK modulation. This caused problems with the current link
adaptation algorithm as the latest possible time to change to 8-PSK (as the link quality is
getting better) is when the GMSK quality reaches the maximum level (if we chose to use
GMSK even when the GMSK link quality was perfect, we would never be able to change
to 8-PSK modulation). With some MSs even this moment is too early and they try to use
8-PSK although it is not robust enough for data transfer in those conditions. Link
adaptation can try to change modulation back to GMSK based on the 8-PSK BEP values
but even then some transmissions are done with 8-PSK. This is not enough for data
transfer to continue in certain (max. 2 dB wide) areas as seen in Figures 33 and 37. This
behavior is illustrated in Figure 54. Despite the non-optimal behavior on the modulation
selection the downlink performance with the optimized LA is improved almost as much
as with newer MSs when comparing to the original LA.
Figure 54. Selection of modulation with same link adaptation version and different MSs
GMSK BEP
8-PSK BEP
C/I, RX-level
BEP
8-PSK used GMSK
used
Change of modulation in
practice
Measured BEP value: 8-
PSK or GMSK BEP
GMSK BEP
8-PSK BEP
C/I, RX-level
BEP
8-PSK used GMSK
used
Desired change of
modulation
Change of modulation in
practice
Measured BEP value:
8-PSK or GMSK BEP
GMSK BEP decreases later
New MSs (Rel’04+SAIC) Older MSs (Rel’04+non-SAIC)
GMSK and 8-PSK used alternately
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9.1.2. Uplink Performance
In laboratory environment uplink throughput performance with the optimized link
adaptation was improved in average by +9% in the whole range of the cell. The behavior
of the optimized link adaptation on uplink was very near the optimal level with all MSs.
The MSs that were not working optimally when the modulation was changed on
downlink were working correctly on uplink direction. The EGPRS coverage in uplink
direction was improved by +5 dB.
The only measurement where optimized LA was not working optimally in UL direction
was the one made in variable C/I scenario. There modulation was changed too early
(when the link quality decreased) to GMSK reducing the performance slightly (Figure
38). In variable RX-level scenario the change of modulation was done exactly in the right
spot and therefore it would make no sense to adjust the link adaptation only for C/I uplink
conditions. If the change of modulation is too early, that doesn’t cause any problems, just
slight decrease in performance. If the change is too late, that can ruin the performance
completely on a certain area.
9.2. Performance in Live Network
In live network the performance improvement can be as clearly seen as in laboratory
conditions. The live measurements were done as drive tests and RX-levels during the
driven route represented well the whole range of the cell: -65 dBm – -105 dBm.
Downlink TCP data throughput during drive tests was improved by +11% and uplink
TCP data throughput by +31%. In downlink direction the biggest improvement on the test
route was observed when link quality was poor. In uplink data transfer the throughput
was improved on almost every part of the route. Also retransmission rate and BLER were
both reduced with the optimized LA.
The behavior of the optimized link adaptation was much more stable than the behavior of
the original LA. The differences in the behavior could be seen particularly in low RX-
levels (-85 – -105 dBm) but also with reasonably good link quality (RX-levels: -70 – -85
dBm): RLC throughput was much more stable resulting in also higher TCP throughput.
Behavior of the optimized link adaptation was very similar in laboratory and live
environment. In live network it seems that the optimized LA is able to improve
performance even more than in laboratory environment. This proves that even if the LA
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optimization work was done in laboratory, the results improve the system performance
also in real networks.
9.3. Further Study Items and Future Improvement
Potential
The results achieved in this thesis are well in accordance with the original objectives. The
main objective was to get link adaptation to operate at ideal level. This was achieved as
the optimized LA is able to use most suitable coding schemes in almost all cases. This
leads to more stable RLC throughput which results in noticeable improvements also on
application level performance.
To be certain that the performance level obtained in this thesis can be reached in all
environments and conditions some further studies should be carried out. Link adaptation
performance should be tested with more MS types as the transceiver performance of MS
has great effect on the LA performance. Also the effect of certain GSM features on LA
(such as frequency hopping) should be analyzed. Analyses in commercial operators’
networks would offer valuable information on the performance of link adaptation in real
environment. The analysis could be carried out by using Key Performance Indicator
(KPI) data from Network Management Subsystem.
After the optimization work there was still some room for improvements. Biggest
improvement potential of the optimized link adaptation is in downlink data transfer with
some older MSs. If we wanted to optimize the system performance further from the link
adaptation point of view, the LA algorithm should be improved e.g. by introducing new
inputs to the algorithm. If RX-level and C/I could be used as criteria when choosing the
modulation, the behavior illustrated in Figure 54 wouldn’t be a problem. The modulation
could be changed earlier to GMSK (when link quality decreases) based on low RX-level
or low C/I ratio. That would prevent the drops in performance with all MSs.
This enhanced algorithm would improve the performance with certain MSs on downlink
but then on the other hand, the performance which is now at the optimum level might go
down in some cases because of too early change to GMSK modulation.
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10. Conclusions
The scope of this thesis was to improve the performance of EGPRS link adaptation. The
optimization work was done with real equipment in laboratory and in live network
environments to maximize the performance improvement in real networks.
First the baseline measurements were executed with the original system to see the areas
where the performance was not optimal. These areas were then thoroughly analyzed to be
able to understand how the system performance could be improved. The changes to the
link adaptation were implemented according to these analyses. Various versions of link
adaptation were created and tested to see which offered the best performance and if the
changes were working as intended. After every new version we were able to reduce the
gap between the implemented and ideal link adaptation.
The final version of the optimized link adaptation was working at the optimum level in
almost all cases. The performance improvement to the original link adaptation could be
clearly seen in laboratory and live network. In laboratory the throughput performance was
improved by +11% in average. Coverage for EGPRS service was improved by 1-6 dB
depending on circumstances. In live network throughput improvement was +11% and
+31% in downlink and in uplink data transfer, respectively.
Although the results with the optimized link adaptation were optimal in almost every
environment there was still room left for improvement with certain MSs. To be able to
meet the optimum performance level with all mobile stations the link adaptation
algorithm could be enhanced further for example by introducing new inputs for LA
algorithm.
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11. References
[1] SYSTRA – GSM System Training (2000), Nokia Networks, p. 229
[2] Hakaste M., Nikula E., Hamiti S. (2002); ”GSM/EDGE Standards Evolution (up
to Rel’4)”; GSM, GPRS and EDGE Performance, Chapter 1, On pages: 3-53, John Wiley & Sons, Ltd.
[3] 3GPP TS 45.001 version 4.5.0 Release 4 (2005); “Physical layer on the radio
path; General description”; Annex A “Reference Configuration”.
[4] Molkdar D., Featherstone W., Larnbotharan, S. (2002) “An Overview of EGPRS:
The Packet Data Component of EDGE”; Electronics & Communication
Engineering Journal, Volume 14, Issue 1, On pages: 21-38.
[5] Furuskar A., Mazur S., Muller F., Olofsson, H. (1999); ”EDGE: Enhanced Data
Rates for GSM and TDMA/136 Evolution”; IEEE Personal Communications
Volume 6, Issue 3, On pages: 56-66.
[6] Ball C.F., Ivanov K., Stockl P., Masseroni C., Parolari S., Trivisonno R. (2004);
”Link Quality Control Benefits from a Combined Incremental Redundancy and
Link Adaptation in EDGE Networks”; Vehicular Technology Conference (VTC) 2004-Spring, Volume 2, On pages: 1004- 1008.
[7] 3GPP TS 43.064 version 4.5.0 Release 4 (2004); “Overall description of the
GPRS radio interface; Stage 2”; Chapter 6.5 Physical RF Layer
[8] Mohan N., Chandrasekaran P., Hmimy H. (2005); “Drive Test Based EDGE
Radio Network Performance Evaluation”; Vehicular Technology Conference
(VTC) 2005-Fall, Volume 3, On pages: 1658- 1661.
[9] Gomez G., Sanchez R., Cuny R., Kuure P., Paavonen T. (2003) “Packet Data
Services and End-user Performance”; GSM, GPRS and EDGE Performance
(Second Edition), Chapter 8, On pages: 307-349, John Wiley & Sons, Ltd.
[10] Nanda S., Balachandran K., Kumar, S. (2000); ”Adaptation Techniques in
Wireless Packet Data Services”; IEEE Communications Magazine Volume 38,
Issue 1, On pages: 54-64.
[11] Lee D.S., Lin C.C. (2002); “Window adaptive TCP for EGPRS networks”; The
5th International Symposium on Wireless Personal Multimedia Communications,
Volume 2, On pages: 853- 857.
[12] Sánchez R., Martinez J., Romero J., Järvelä R. (2002); “TCP/IP Performance
over EGPRS network” Vehicular Technology Conference (VTC) 2002-Fall,
Volume 2, On pages: 1120-1124.
[13] Huang D., Shi J.J. (2000); ”TCP over packet radio”; Emerging Technologies Symposium: Broadband, Wireless Internet Access, IEEE
[14] Propsim C8 Operation Manual (2003); “Channel Modeling Theory”; Chapter 8
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[15] Romero J., Martinez J., Nikkarinen S., Moisio M. (2003) ; “GPRS and EGPRS
Performance”; GSM, GPRS and EDGE Performance (Second Edition), Halonen
T, Romero J., Melero J., Chapter 7, On pages: 235-305, John Wiley & Sons, Ltd.
[16] Featherstone W., Molkdar D. (2001); “Impact of Imperfect Link Adaptation in
EGPRS”; 3G Mobile Communication Technologies, Second International Conference, Conf. Publ. No. 477, On pages: 277-281.
[17] Ericsson White Paper (2003); “EDGE, Introduction of high-speed data in
GSM/GPRS networks”; www.ericsson.com/technology/whitepapers/edge_wp_technical.pdf
[18] 3GPP TS 44.060 version 4.23.0 Release 4 (2005); “Radio Link Control/Medium
Access Control protocol”; Chapter 8.1, Tables 8.1.1.1. and 8.1.1.2.
[19] Featherstone W., Molkdar D. (2000); “System Level Performance Evaluation of
EGPRS in GSM Macro-cell Environments”; Vehicular Technology Conference
(VTC) 2000-Fall, Volume 6, On pages: 2653-2660.
[20] 3GPP TS 45.008 version 4.17.0 Release 4 (2005); “Radio subsystem link
control”; Annex D, Table 3.
[21] Propsim fading simulator: http://www.propsim.com
[22] 3GPP TS 45.005 version 4.18.0 Release 4 (2005); ”Radio transmission and reception”; C3.3 Typical Urban (TU) propagation model on page 79.
[23] Link Adaptation training material (2005); “Link Adaptation - Introduction”;
Nokia Internal document
[24] Pirhonen R., Salmenkaita M. (2002); “Link Performance Enhancements”; GSM,
GPRS and EDGE Performance, Halonen T, Romero J., Melero J., Chapter 10, On
pages: 343-362, John Wiley & Sons, Ltd.
[25] Nemo Outdoor drive test tool: http://www.nemotechnologies.com
[26] Microsoft Internet Explorer: http://www.microsoft.com/windows/ie
[27] Heliste H. (2003); “EGPRS Uplink Link Adaptation Challenge”; Nokia Internal document.
[28] Kobylinski R., Ghosh A., Mostafa A. , Whitehead J. (2005); “EDGE terminal
with interference cancellation and spatial diversity processing”; International Conference on Wireless Networks, Communications and Mobile Computing;
Volume 2, On pages: 884- 889.
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Appendix A:
3GPP TS 45.005
Typical Urban (TU) 6-tap propagation model, variant 1 [22]
Tap number Relative time (µs)
Average relative
power (dB)
Doppler
spectrum
1 0,0 -3 Classical
2 0,2 0 Classical
3 0,5 -2 Classical
4 1,6 -6 Classical
5 2,3 -8 Classical
6 5,0 -10 Classical
3GPP TUx Propagation Model
-40
-30
-20
-10
0
-1 0 1 2 3 4 5 6
Delay [us]
Strength (dB)
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Appendix B:
3GPP TS 45.002 version 4.8.0 Release 4
MS classes for multislot capability
Multislot Maximum number of slots
class Rx Tx Sum
1 1 1 2
2 2 1 3
3 2 2 3
4 3 1 4
5 2 2 4
6 3 2 4
7 3 3 4
8 4 1 5
9 3 2 5
10 4 2 5
11 4 3 5
12 4 4 5
13 3 3 NA
14 4 4 NA
15 5 5 NA
16 6 6 NA
17 7 7 NA
18 8 8 NA
19 6 2 NA
20 6 3 NA
21 6 4 NA
22 6 4 NA
23 6 6 NA
24 8 2 NA
25 8 3 NA
26 8 4 NA
27 8 4 NA
28 8 6 NA
29 8 8 NA
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Appendix C:
Reliability of the measurement results
The measurements for this thesis were done with quite a low number of samples per one
measurement. This was mainly due to the fact that the measurements were time-
consuming and the number of different kinds of measurements was large. If test
automation could have been used, the number of samples could have been much higher.
Now the measurements were done with only 3-5 samples per one measurement.
Therefore it’s not possible to prove the statistical reliability of the results. By analyzing
the results it can be seen that in practice the results should present quite reliably the real
performance of the system.
Here UL throughput measurement results are analyzed as an example of the measurement
results. Figure C1 presents all the samples from UL throughput measurement in variable
RX-level scenario. The same measurement values are presented also in Table C1. In this
measurement 3 samples per RX-level and per link adaptation version were measured.
It can be clearly seen in Figure C1 that the results of different samples (in same RX-level
and with same LA version) don’t differ essentially. There is some deviation between the
samples but in all cases all samples of one link adaptation version are clearly
differentiated from the respective samples of other LA version if there is some difference
in average value. The same kind of behavior can be seen in all measurements.
Although the absolute difference between the performance of the different link adaptation
versions can’t be precisely determined with such a low number of samples, the overall
improvement of optimized link adaptation in certain areas (in this measurement when
RX-level < -90 dBm) can be clearly seen and can be considered as reliable.
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UL Throughput, Variable RX-level, 2 TSL
0%
20%
40%
60%
80%
100%
120%
-110 -105 -100 -95 -90 -85 -80 -75 -70 -65
RX-Level (dBm)
Throughput (relative)
Original LA meas. 1 Original LA meas. 2 Original LA meas. 3Optimized LA11 meas. 1 Optimized LA11 meas. 3 Optimized LA11 meas. 3Average of Original LA Average of Optimal LA11
Figure C1: Uplink FTP throughput measurement in variable RX-level scenario with all measured
samples
Table C1: Uplink FTP throughput measurement values (relative to maximum throughput) in
variable RX-level scenario
RX-level (dBm) O
riginal LA
meas. 1
Original LA
meas. 2
Original LA
meas. 3
Average of
Original LA
Optimized
LA11
meas.1
Optimized
LA11
meas.2
Optimized
LA11
meas.3
Average of
Optimized
LA11
-104 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
-102 0.0% 0.0% 0.0% 0.0% 7.2% 6.5% 9.0% 7.6%
-100 0.0% 0.0% 0.0% 0.0% 16.8% 16.6% 14.2% 15.9%
-97 3.4% 2.5% 3.0% 3.0% 23.2% 23.5% 22.1% 22.9%
-95 12.3% 7.8% 7.8% 9.3% 25.6% 23.8% 26.6% 25.3%
-92 18.6% 19.2% 18.8% 18.9% 38.3% 38.9% 37.6% 38.3%
-90 49.8% 50.7% 50.3% 50.3% 50.7% 52.1% 51.1% 51.3%
-88 51.3% 50.2% 50.8% 50.8% 60.1% 64.7% 63.4% 62.7%
-85 75.6% 78.6% 78.4% 77.5% 78.1% 76.6% 77.1% 77.3%
-80 98.3% 96.3% 96.9% 97.2% 97.9% 99.4% 98.4% 98.6%
-75 100.1% 100.3% 98.4% 99.6% 99.2% 98.4% 98.7% 98.8%
-70 98.6% 99.8% 100.2% 99.5% 99.4% 99.3% 98.5% 99.1%
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Company Confidential Appendix D:
Specification for Modulation and MCS-Selection Tables of EGPRS Link Adaptation
Final optimized LA (version LA11)
→ Relationship of GMSK and 8PSK BEP is changed (Table 12 in EGPRS IS)
→ Modulation selection table is changed (Table 13 in EGPRS IS) → MCS selection table for GMSK is changed (Table 14 in EGPRS IS)
→ MCS selection table for 8-PSK is changed (Table 15 in EGPRS IS)
New Table:
Reported
GMSK
MEAN_BEP
Estimation for
8-PSK
MEAN_BEP
Reported
8-PSK
MEAN_BEP
Estimation for
GMSK
MEAN_BEP
0 – 7 0 0 7
8 – 19 1 1 18
20 – 21 2 2 21
22 – 23 3 3 23
24 – 25 4 4 25
26 – 27 5 5 27
28 6 6 28
29 – 30 7 7 29
31 8 8 – 31 31
Table 12. Relationship of GMSK and 8PSK mean BEP.
Old Table:
Reported
GMSK
MEAN_BEP
Estimation for
8-PSK
MEAN_BEP
Reported
8-PSK
MEAN_BEP
Estimation for
GMSK
MEAN_BEP
0 – 7 0 0 3
8 – 9 1 1 8
10 – 11 2 2 10
12 – 13 3 3 12
14 – 15 4 4 14
16 – 18 5 5 17
19 – 20 6 6 19
21 – 23 7 7 22
24 – 25 8 8 24
26 – 28 9 9 27
29 – 30 10 10 29
31 11 11-31 31
Table 12. Relationship of GMSK and 8PSK mean BEP.
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New table:
8PSK CV_BEP
8PSKMEAN_BEP
0 1 2 3 4 5 6 7
0 0 0 0 0 0 0 0 0
1 3 3 3 3 3 2 2 2
2 7 7 6 6 5 5 4 3
3 9 9 8 8 7 7 6 5
4 11 11 9 9 8 8 7 7
5 15 15 14 13 12 10 9 8
6 16 16 15 14 13 12 11 9
7 18 18 16 15 14 13 12 10
8 – 31 32 32 32 32 32 32 32 32
Table 13. GMSK mean BEP limits for modulation selection.
Old table:
8PSK CV_BEP
8PSKMEAN_BEP
0 1 2 3 4 5 6 7
0 0 0 0 0 0 0 0 0
1 6 6 6 6 6 6 5 5
2 9 9 9 9 9 9 7 6
3 32 32 32 32 21 12 11 8
4 32 32 32 32 32 20 13 12
5 32 32 32 32 32 24 21 21
6 – 31 32 32 32 32 32 32 32 32
Table 13. GMSK mean BEP limits for modulation selection.
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New Table:
GMSK_CV_BEP
GMSK_MEAN_BEP
0 1 2 3 4 5 6 7
0 – 5 1 1 1 1 1 1 1 1
6 2 2 2 1 1 1 1 1
7 2 2 2 2 2 2 1 1
8 – 9 2 2 2 2 2 2 2 2
10 3 3 3 2 2 2 2 2
11 3 3 3 3 3 2 2 2
12 – 21 3 3 3 3 3 3 3 3
22 – 31 4 4 4 4 4 4 4 4
Table 14. MCS selection table for GMSK.
Old Table:
GMSK_CV_BEP
GMSK_MEAN_BEP
0 1 2 3 4 5 6 7
0 – 3 1 1 1 1 1 1 1 1
4 2 2 1 1 1 1 1 1
5 2 2 2 1 1 1 1 1
6 2 2 2 2 2 2 1 1
7 – 9 2 2 2 2 2 2 2 2
10 – 19 3 3 3 3 3 3 3 3
20 – 31 4 4 4 4 4 4 4 4
Table 14. MCS selection table for GMSK.
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New Table:
8-PSK_CV_BEP
8-PSK_MEAN_BEP
0 1 2 3 4 5 6 7
0 – 3 5 5 5 5 5 5 5 5
4 6 5 5 5 5 5 5 5
5 6 6 5 5 5 5 5 5
6 6 6 6 5 5 5 5 5
7 6 6 6 5 5 5 5 5
8 6 6 6 6 5 5 5 5
9 6 6 6 6 6 5 5 5
10 – 16 6 6 6 6 6 6 6 6
17 – 21 7 7 7 7 7 7 7 7
22 – 28 8 8 8 8 8 8 8 8
29 – 31 9 9 9 9 9 9 9 9
Table15. MCS selection table for 8-PSK.
Old Table:
8-PSK_CV_BEP
8-PSK_MEAN_BEP
0 1 2 3 4 5 6 7
0 – 3 5 5 5 5 5 5 5 5
4 6 5 5 5 5 5 5 5
5 6 6 5 5 5 5 5 5
6 6 6 6 5 5 5 5 5
7 6 6 6 5 5 5 5 5
8 6 6 6 6 5 5 5 5
9 6 6 6 6 6 5 5 5
10 – 16 6 6 6 6 6 6 6 6
17 – 21 7 7 7 7 7 7 7 7
22 – 25 8 8 8 8 8 8 8 8
26 – 31 9 9 9 9 9 9 9 9
Table15. MCS selection table for 8-PSK.