capacity and quality of single cell wimax network for voip .... capacity and...wimax 802.16e-2005 is...

Capacity and Quality of Single Cell WiMAX Network for VoIP Application

Budi Setiyanto, Esmining Mitarum, Sigit Basuki Wibowo Dept. of Electrical Engineering and Information Technology, Faculty of Engineering, Gadjah Mada University

Jl. Grafika 2, Yogyakarta 55281 Indonesia [email protected] [email protected] [email protected]

Abstract— Voice over Internet Protocol (VoIP) is expected to be implemented in the next generation communication networks. WiMAX 802.16e-2005 is an IP-based technology which provides specific service class for VoIP, called ertPS, in order to ensure bandwidth availability. The purpose of this research is to analyze capacity and quality of VoIP over WiMAX network for different types of codec. Hence, a single cell mobile WiMAX network with OFDMA 5 MHz system profile was created using simulator. All users are set to run VoIP application. VoIP capacity and quality are analyzed by referring to parameters like MOS, jitter, end-to-end delay, and packet loss. The codecs used are G.711 and G.729. The users are categorized into fixed user, pedestrian, and vehicular. The result informs that 5 MHz mobile WiMAX network is able to support up to eight VoIP users using G.711 with bit rate allocation for each user is 150 kbps, while using G.729 with bit rate allocation for each user is 125 kbps, 5 MHz mobile WiMAX network is able to support up to twelve VoIP users. Keywords- VoIP, WiMAX, voice quality, network capacity, codec

I. INTRODUCTION Voice-over Internet Protocol (VoIP) is the

transmission of voice using the Internet Protocol (IP) to carry packetized voice data [1], so the telephone connection over IP network could be done. Mobile WiMAX also known as IEEE 802.16e-2005 is a scalable, IP-based, high speed communications network delivering a robust air link, higher throughput rates at longer distances, increased spectral efficiency, non-line of sight (NLOS) coverage, QoS classes, security and mobility [2]. As WiMAX networks are all-IP networks, voice services over WiMAX are implemented as Voice over IP [3].

In VoIP communication, the quality of voice is affected by the mobilization of subscriber stations and the VoIP codecs. Mean Opinion Score (MOS) can be used to measure the quality of voice. The MOS is a subjective quality score that ranges from 1 (worst) to 5 (best) and is obtained by conducting subjective surveys [4]. The end-to-end network delay, jitter, and packet loss are also affected by the mobilization of subscriber stations and the VoIP codecs.

In this paper, the capacity and quality of single cell WiMAX network for VoIP application will be analyzed and discussed. The effects on end-to-end delay, packet loss probability, and jitter for calling pairs using VoIP over WiMAX will be analyzed. Beside these parameters, environmental factors, such as distances between base stations and mobile workstations and mobile user’s moving speed, are also important and are concerned to

affect QoS. Therefore, scenarios comparing fixed and mobile calling pairs using two different types of codec will be also discussed.

The rest of this paper is organized as follows. Section II presents overview of QoS in mobile WiMAX, capacity of WiMAX, VoIP codecs and the key performance indicators of WiMAX network. The simulation model of WiMAX network is presented in Section III. Simulation results are presented in Section IV and Section V concludes the paper, with outline of future work.

II. OVERVIEW

A. Quality of Services in Mobile WiMAX To support a wide variety of applications, mobile

WiMAX standard defines five different scheduling services that should be supported by the base station MAC scheduler for data transport over a connection, they are Unsolicited Grant Service (UGS), Extended Real-Time Polling Service (ertPS), Real-Time Polling Service (rtPS), Non Real-Time Polling Service (nrtPS), and Best Effort (BE). UGS and ertPS service types can be used to support VoIP application [10]. The ertPS has an advantage over UGS because it uses silence suppression method. Silence Suppression (SS) is a technique used in many codecs in order to reduce VoIP bandwidth [5].

B. WiMAX Network Capacity Network capacity is defined as the number of

subscribers which can be served by a single cell, each of the subscribers should meet the requirements, while cell capacity is the ability of system to deliver the information per unit time (symbol per second, sps).

To measure the capacity of the WiMAX physical layer, the number of symbols generated in a second should be known. The physical layer of WiMAX has 5 ms frame duration, each frame has 48 OFDM symbols, with 44 OFDM symbols available for data transmission [6]. From the information above, in a second, there are 200 frames and 8800 symbols available for data transmission.

The downlink and uplink capacity depends on the DL: UL ratio and sub-channelization scheme if the duplexing operation used is TDD. For example, the ratio of DL: UL is 1:1 so the downlink and uplink capacity determined as follows.

𝐶𝐷𝐿 = 12×8800×𝑁𝑑𝑎𝑡𝑎𝐷𝐿 (1) 𝐶𝑈𝐿 = 12×8800×𝑁𝑑𝑎𝑡𝑎𝑈𝐿 (2)

CITEE 2012 Yogyakarta, 12 July 2012 ISSN: 2088-6578

DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter 257

The value of NdataDL and NdataUL is the number of data sub-carriers which determined by the sub-channelization scheme. The value of NdataDL dan NdataUL for PUSC sub-channelization can be seen in Table 1 [7]. Table 1. Uplink and downlink PUSC OFDMA permutation for 5

MHz BW Direction Nsubcarriers Nused Ndata Downlink 512 421 360

Uplink 512 409 272

C. Codec A voice codec is used to convert the analogue voice

waves to digital pulses and vice versa. There are different codec types based on the selected sampling rate, data rate, and implemented compression algorithm. The choice of codec used is important because it determines the required bandwidth per call. The codecs used in this research are G.711 and G.729 because they are widely used in the wireless networks. The sampling rate of voice with both codecs is 8 kHz. In G.711, each sample is encoded with 8 bits resulting 64 kbps bit rate and offers very good voice quality. The samples can be collected into frames every 10 ms. The G.729 also generate voice frames every 10 ms contains 80 voice samples. The comparison between G.729 and G.711 is presented in Table 2.

Table 2. G.711 vs. G729 Codec Algorithm Bit Rate (kbps)

Sample Time (ms)

Frame Size (bit)

Look-ahead delay(ms)

G.711 PCM 64 10 640 - G.729 CS- ACELP 8 10 80 5

D. Key Performance Indicators Key Performance Indicators are used to measure the

performance of mobile WiMAX networks. In this case, the appropriate metrics are used as indicators. There are 4 metrics used as indicators.

a. MOS Mean Opinion Score (MOS) is method used to

measure the quality of voice in IP network based on ITU-T P.800. The MOS is a subjective quality score because the average of voice quality is measured based on human perception. The range of MOS values are 1 (very annoying), 2 (annoying), 3 (slightly annoying), 4 (perceptible but not annoying) and 5 (imperceptible) [5].

b. Jitter Jitter is a variation in packet transit delay caused by

queuing, contention and serialization effects on the path through the network [1]. Negative jitter is caused by arrived packets with lead in time period while positive jitter is caused by arrived packets with lag in time period, both degrade the voice quality [8]. Jitter levels should be less than 50 ms [1].

c. E2E Delay E2E delay defined as the time taken by application

from application layer in sender to application layer in receiver. Recommendations for one-way transmission time based ITU-T G.114 is presented in Table 3.

Table 3. Recommendations for one-way transmission time based ITU-T G.114 [9]

Range in Milisecond ITU-T Recommendation

0 -150 ms Acceptable for most user application

150 -400 ms

Acceptable provided that administrators are aware of the transmission time and its impact on transmission quality of user application.

>400 ms

Unacceptable for general network planning purpose, it is recognized that in some exceptional cases this limit will be exceeded.

d. Packet loss Packet loss occurs when some or all packets fails to

reach their destination. It can occur because of network congestion or error connectivity between endpoints. The recommended packet loss for VoIP application should be no more than 1% [1].

Based on the standards and some recommendations,

the metrics values used to measure the mobile WiMAX network performance are determined. Table 4 presents the minimum metric values for VoIP application to ensure the QoE of users.

Table 4. Minimum metric value used in the research MOS Packet Loss Jitter E2Edelay

> 2,75 < 1 % < 20 ms < 400 ms

III. WIMAX NETWORK SIMULATION MODEL DESIGN

Fig. 1 – Network topology

This research uses OPNET Modeler version 14.0 which has mobile WiMAX module in it [10]. It is assumed that a service provider has implemented 5 MHz mobile WiMAX network in some area. The network consists of a cell with one BS, the BS is connected to the IP network which is connected to a server. Those three components represent the service provider network. (Fig.1). A cell of the network has 0.5 km radii.

The cell has three different zones with different colours, each zone represents different modulation scheme and coding rate. The modulation scheme and coding rate of every SS are determined by the position of SS in the cell (Table 5).

ISSN: 2088-6578 Yogyakarta, 12 July 2012 CITEE 2012

258 DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter

Table 5.Modulation scheme and coding rate based on color zone

Color Modulation Coding Rate Green 64-QAM 3/4 Orange 16-QAM 1/2 Yellow QPSK 1/2

The parameter of WiMAX physical layer used in

simulation is presented in Table 6.

Table 6. OFDM Parameters Used in WiMAX [11]

Parameter Mobile WiMAX

Scalable OFDMA-PHY 5 MHz

FFT size 512 Number of used data subcarriers 360 Number of pilot subcarriers 60 Number of guardband subcarriers 92 Cyclic Prefix 1/8 Oversampling rate 28/25 Channel bandwidth (MHz) 5 Subcarrier frequency spacing (kHz) 10,94 Useful symbol time (µs) 91,4 Guard time assuming 12,5% (µs) 11,4 OFDM symbol duration(µs) 102,9 TTG (µs) 100,8 RTG (µs) 302,4 Number of OFDM symbols in 5 ms frame 48 DL : UL ratio 1:1 Subchannel scheme PUSC

Table 7.MAC Service Class Definitions Attribute G.711 G.729

Scheduling type ertPS ertPS Max. Sustained Traffic Rate (kbps) 150 125 Min. Reserved Traffic Rate (kbps) 150 125 Max. Latency (ms) 10 10

Other parameters are used to determine the service

classes are presented in Table 7. Maximum Sustained Traffic Rate (MSTR) and Minimum Reserved Traffic Rate (MRTR) parameters on ertPS class are arranged in the same value to guarantee the data rate for a given service flow.

There are six simulation scenarios combined from subscriber types and the voice codecs. Voice over IP Call (PCM) quality which is available in the simulator is used to generate the voice traffic flow.

IV. SIMULATION RESULTS AND DISCUSSION

A. System Capacity and Network Capacity Table 8 presents the system capacity obtained from

the simulation and calculation based on Equation (1) and (2). The simulation result of UL and DL capacity are different from the calculation. The simulation results are in lower value than the calculation because of the longer OFDM frame duration. The OFDM frame duration is more than 5 ms, it caused by TTG and RTG. From the Table 6, the number of OFDM symbols are 48, each symbol duration is 102.9 µs, so the total duration for an OFDM frame is 4939.2 µs. Since the given value of TTG is 100.8 and the RTG is 302.4, the duration of an OFDM frame becomes 5342.4 µs or 5.3424 ms. It causes the

number of frames in a second to decrease as well as the capacity of WiMAX system.

Table 8.UL and DL Capacity of 5 MHz WiMAX Network Capacity Calculation Result Simulation Result

Uplink (sps) 1196800 1193600 Downlink (sps) 1584000 1512000 Total (sps) 2780800 2705600 The capacity of the six scenarios is presented in Table

9. The results show that the network capacity is affected by the codec used. G.729 gives more capacity than G.711.

Table 9. Network capacity of six scenarios Scenario Codec SS Type Network Capacity (SS) MOS

1 G.711 Pedestrian 8 2,96 2 G.711 Vehicular 8 2,81 3 G.711 Fixed 8 2.77 4 G.729 Pedestrian 12 2,80 5 G.729 Vehicular 12 2,81 6 G.729 Fixed 12 2.90

B. The Effect of SS Types on Quality of Service

Fig 2 –Average jitter vs. total users with G.711

Fig 3 –Average jitter vs. total users with G.729

The average jitters vs. total users with G.711 and G.729 are shown in Fig. 2 and 3, respectively. The average jitters of G.711 for vehicular users are higher than that for the pedestrian and fixed users. The average jitters of G.729 for pedestrian and vehicular users are almost the same. The average jitters for fixed users are lower than that for pedestrian and vehicular. When the users exceed 12, the average jitters of vehicular users become higher than that of fixed and pedestrian users. The trend of jitter in G.711 codec is positive while in G.729 is negative.



E2E delay for vehicular users with G.711 is higher than that for pedestrian and fixed users, as shown in Fig. 4. In G.729, the E2E delay values for all types of user are almost the same but when the users exceed 12, the E2E delay for vehicular users is higher than that for pedestrian and fixed users, as shown in Fig. 5.

Fig. 4 – Average ETE delay vs. total users with G.711

Fig. 5 – Average ETE delay vs. total users with G.729

Fig. 6 shows that the packet loss with G.711 is below 1 %, but when the users exceed 10, the packet loss increases. Packet loss for users with G.729 is lower than 0.5 % and it increases until 4.5% when the network serves 14 users. Fig. 7 shows the result of packet loss of users with G.729.

Fig. 6 – Average packet loss vs. total users with G.711

Fig. 7– Average packet loss vs. total users with G.729

Fig. 8 shows that most of the average MOS for fixed and pedestrian users is slightly higher than that for vehicular users. Most of the MOS of vehicular users is lower than that of pedestrian and fixed users because most of the jitter, E2E delay, and packet loss of vehicular users are higher than that of pedestrian and fixed users. The highest MOS of fixed and pedestrian users is 3.64, while the highest MOS of vehicular user is 3.50. It attained when the number of user is 1. When the users exceed 9, the MOS is below 2.75.

Fig. 8 – Average MOS vs. total users with G.711

Fig. 9 shows the similarity of average MOS for vehicular and fixed users using G.729. The G.729 requires 5 ms look-ahead delay before producing any new frame, it helps reducing the effect of negative jitter. G.729 offers better performance for vehicular and fixed than that for pedestrian. The highest MOS of vehicular and fixed users is 3.03, while for pedestrian is 3.01. The increasing user causes the decreasing MOS with small decrement. When the users exceed 13, the MOS is below 2.75

Fig. 9 – Average MOS vs. total users with G.729



C. The Effects of Codec Used on Quality of Service Fig. 10, Fig. 11, and Fig. 12 show that the G.711 has

steeper graph of jitter value rise as well as E2Edelay and packet loss, compared to G.729, in term of number of SS. It indicates that as the number of users increases, G.711 will result in more significant increase in jitter value, E2Edelay, and packet loss. It arises from the fact that G.711 has bigger frame size (640 bits per frame) than G.729 (80 bits per frame) and by remembering that bigger frame size leads to faster occurrence of congestion in the network whenever the number of user increases. Congestion in the network itself has adverse effects, i.e. enlarging E2Edelay and jitter, as well as the possibility of occurrence of packet dropping in that network.

Fig. 10 – Average jitter vs. total users in six scenarios

Fig. 11 – Average E2Edelay vs. total users in six scenarios

Fig. 12 – Average packet loss vs. total users in six scenarios

Fig. 13 shows that as the number of user increases, MOS value dropped more drastically in scenario with G.711 than that with G.729. Voice quality is influenced by jitter, E2Edelay, and packet loss: the bigger jitter, E2Edelay and packet loss will result in MOS value decrease.

Highest value of MOS attained by G.711 is 3.64, while G.729 is only 3.03. However, G.729 has advantages, i.e. lower BW requirement and stable MOS.

Fig. 13 – Average MOS vs. total users in six scenarios

V. CONCLUSION AND FUTURE WORK From the analysis of simulation results, some

conclusions can be drawn as follow: (1) Average jitter, E2Edelay, and packet loss for vehicular users are bigger than that for pedestrian and fixed. (2) G.711 offers better voice quality for pedestrian and fixed users, whereas G.729 is better for vehicular and fixed users. (3) As the number of users’ increases, G.711 will result in more significant increase in jitter value, E2Edelay, and packet loss, compared to G.729. (4) As the number of users’ increases, G.729 will result in more stable MOS value, compared to G.711. (5) Network capacity of mobile WiMAX 5 MHz for VoIP application with G.711 codec and 150 kbps BW allocation is 8 users, either pedestrian, fixed or vehicular (6) Network capacity of mobile WiMAX 5 MHz for VoIP application with G.729 codec and 125 kbps BW allocation is 12 users, either pedestrian, fixed, or vehicular.

In future research, we have a plan to analyze the performance of video streaming application scenarios for both mobile and fixed users.

REFERENCES [1] WF, 2010, WiMAX VoIP Solutions for 4G

Networks, WiMAX Forum. [2] Awal, M.A., and L. Boukhatem, 2009, WiMAX and

End-toEnd QoS Support, White Paper, University of Paris.

[3] Adhicandra, I., 2010, Measuring Data and VoIP Traffic in WiMAX Networks, Journal of Telecommunications, Volume 2, Issue 1, April 2010.

[4] Ali, A.A., S. Vassilaras, and K. Ntagkounakis, 2009, A Comparative Study of Bandwidth Requirements of VoIP Codecs Over WiMAX Access Networks, 3rd International Conference on Next Generation Mobile Applications, Services and Technologies.

[5] WF, 2006, Mobile WiMAX – Part I: A Technical Overview and Performance Evaluation, WiMAX Forum.



[6] ICST, 2006, Mobile WiMAX from OFDM-256 to SOFDMA, ICS Telecom.

[7] Kundu, A. et al., 2010, Comparison of VoIP Performance over WiMAX, WLAN, and WiMAX-WLAN Integrated Network Using OPNET, Communications in Computer and Information Science Volume 90 Part 2.

[8] ITU-TR G.114, 2003, One Way Transmission Time, ITU-T Recommendation.

[9] OPNET Technologies, http:/www.opnet.com [10] Andrews, J.G., A. Ghosh, and R. Muhamed, 2007,

Fundamental of WiMAX: Understanding Broadband Wireless Networking, Prentice Hall, New Jersey.



CITEE2012

PROCEEDINGS OFINTERNATIONAL CONFERENCE ON

INFORMATION TECHNOLOGYAND

ELECTRICAL ENGINEERING

Yogyakarta, IndonesiaJuly 12, 2012

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DEPARTMENT OF ELECTRICAL ENGINEERINGAND INFORMATION TECHNOLOGY

FACULTY OF ENGINEERING

GADJAH MADA UNIVERSITY

20

12

Department of Electrical Engineering and Information TechnologyFaculty of Engineering, Gadjah Mada UniversityJalan Grafika no. 2, Kampus UGMYogyakarta, 55281, Indonesia

ISSN: 2088-6578

CITEE 2012 ISSN: 2088-6578

PROCEEDINGS OF INTERNATONAL CONFERENCE ON

INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING

Yogyakarta, 12 July 2012

DEPARTMENT OF ELECTRICAL ENGINEERING AND INFORMATION TECHNOLOGY

FACULTY OF ENGINEERING GADJAH MADA UNIVERSITY


ii DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter

ORGANIZER 2012

Technical Program Committee Chair (cont.)

Andreas Timm-Giell (Universität Hamburg-Harburg Germany)

Ryuichi Shimada (Tokyo Institute of Technology, Japan)

Ismail Khalil Ibrahim (Johannes Kepler University Linz, Austria)

Kang Hyun Jo (University of Ulsan, Korea)

David Lopez (King’s College London, United Kingdom)

Martin Klepal (Cork Institute of Technology, Ireland)

Tamotsu Nimomiya (Nagasaki University, Japan)

Ekachai Leelarasmee (Chulalongkorn University, Thailand)

Marteen Weyn (Artesis University College, Belgium)

Chong Shen (Hainan University, China)

Haruichi Kanaya (Kyushu University, Japan)

Ramesh K. Pokharel (Kyushu University, Japan)

Ruibing Dong (Kyushu University, Japan)

Kentaro Fukushima (CRIEPI, Japan)

Mahmoud A. Abdelghany (Minia University, Egypt)

Sunil Singh (G B Pant University of Agriculture & Technology, India)

Abhishek Tomar (G B Pant University of Agriculture & Technology, India)

Lukito Edi Nugroho (Universitas Gadjah Mada, Indonesia)

Umar Khayam (Institut Teknologi Bandung, Indonesia)

Anton Satria Prabuwono (Universiti Kebangsaan Malaysia, Malaysia)

Eko Supriyanto (Universiti Teknologi Malaysia, Malaysia)

Kamal Zuhairi Zamli (Universiti Sains Malaysia, Malaysia)

Sohiful Anuar bin Zainol Murod (Universiti Malaysia Perlis, Malaysia )

Advisory Board

F. Danang Wijaya

Risanuri Hidayat

General Chair

Widyawan

Chair

Eka Firmansyah

Indriana Hidayah

Eny Sukani Rahayu

Avrin Nur Widyastuti

Bimo Sunarfri Hantono

Sigit Basuki Wibowo

Budi Setiyanto

Ridi Ferdiana

Yusuf Susilo Wijoyo

Adhistya Erna Permanasari

Prapto Nugroho

Muhammad Nur Rizal

Selo Sulistyo

Sunu Wibirama

Lilik Suyanti

Indria Purnamasari

Reviewer

Adhistya Erna Permanasari

Agus Bejo

Avrin Nur Widyastuti

Bambang Sugiyantoro

Bambang Sutopo

Bimo Sunarfri Hantono

Bondhan Winduratna

Budi Setiyanto

Danang Wijaya

Eka Firmansyah

Enas Duhri Kusuma

Eny Sukani Rahayu

Harry Prabowo

Indriana Hidayah

Insap Santosa

Isnaeni

Iswandi

Litasari

Lukito Edi Nugroho

Noor Akhmad Setiawan

Prapto Nugroho

Ridi Ferdiana

Risanuri Hidayat

Rudy Hartanto

Samiadji Herdjunanto

Sarjiya

Sasongko Pramono Hadi

Selo

Sigit Basuki Wibowo

Silmi Fauziati

Suharyanto

Sujoko Sumaryono

Sunu Wibirama

T. Haryono

Teguh Bharata Adji

Wahyu Dewanto

Wahyuni

Warsun Nadjib

Widyawan

Yusuf Susilo Wijoyo


DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter v

Table of Contents Inner Cover i

Organizer ii

Foreword iii

Schedule iv

Table of Contents v

1. I-ALG #11

Enabling Real-time Alert Correlation Using Complex Event Processing 1

Hichem Debbi, Bilal Lounnas, and Abdelhak Bentaleb

2. I-JPN #11

Detection and Verification of Potential Peat Fire Using Wireless Sensor Network and UAV 6

Rony Teguh, Toshihisa Honma, Aswin Usop, Heosin Shin, and Hajime Igarashi

3. I-IND #11

Data Mining Application to Reduce Dropout Rate of Engineering Students 11

Munindra Kumar Singh, Brijesh Kumar Bharadwaj, and Saurabh Pal

4. I-THA #11

Usability Standard and Mobile Phone Usage Investigation for the Elderly 15

V. Chongsuphajaisiddhi, V. Vanijja, and O. Chotchuang

5. I-Jkrt #11

Test on Interface Design and Usability of Indonesia Official Tourism Website 21

Anindito Yoga Pratama, Dea Adlina, Nadia Rahmah Al Mukarrohmah, Puji Sularsih,

and Dewi Agushinta R.

6. I-Jkrt #12

Data Warehouse for Study Program Evaluation Reporting Based on Self Evaluation

(EPSBED) using EPSBED Data Warehouse Model: Case Study Budi Luhur University

25

Indra, Yudho Giri Sucahyo, and Windarto

7. I-Bndg #11

Denial of Service Prediction with Fuzzy Logic and Intention Specification 32

Hariandi Maulid

8. I-Smrg #11

Integrating Feature-Based Document Summarization as Feature Reduction in Document

Clustering

39

Catur Supriyanto, Abu Salam, and Abdul Syukur

9. I-Smrg #12

A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR)

Algorithm

43

Erika Devi Udayanti, Yun-Huoy Choo, Azah Kamilah Muda, and Fajar Agung Nugroho

10. I-Smrg #13

Loose-Coupled Push Synchronization Framework to Improve Data Availability in Mobile

Database

48

Fahri Firdausillah, and Norhaziah Md. Salleh

11. I-Smrg #14

Feature Extraction on Offline Handwritten Signature using PCA and LDA for Verification

System

53

Fajrian Nur Adnan, Erwin Hidayat, Ika Novita Dewi, and Azah Kamilah Muda

12. I-UGM #11

Cognitive Agent Based Modeling of a Question Answering System 58

Eka Karyawati, and Azhari SN

13. I-UGM #12

GamaCloud: The Development of Cluster and Grid Models based shared-memory and MPI 65

Mardhani Riasetiawan

14. I-TEIb #11

Sub-Trajectory Clustering for Refinement of a Robot Controller 70

Indriana Hidayah

15. I-TEIb #12

Transfer Rules Algorithm for Hierarchical Phrase-based English-Indonesian MT Using ADJ

Technique

74

Teguh Bharata Adji

16. P-IRI #11

Investigation of Insulation Coordination in EHV Mixed Line 77

A.Eyni, and A.Gholami


DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter vi

17. P-IND #11

Unbalance and Harmonic Analysis in a 15-bus Network for Linear and Nonlinear Loads 82

T.Sridevi, and K.Ramesh Reddy

18. P-Bntn #11

The Maximizing of Electrical Energy Supply for Production of Steel Plant through Fault

Current Limiter Implementation

88

Haryanta

19. P-Smrg #11

Modelling and Stability Analysis of Induction Motor Driven Ship Propulsion 93

Supari, Titik Nurhayati, Andi Kurniawan Nugroho, I Made Yulistya Negara, and

Mochamad Ashari

20. P-Pwt #11

A New Five-Level Current-Source PWM Inverter for Grid Connected Photovoltaics 98

Suroso, Hari Prasetijo, Daru Tri Nugroho, and Toshihiko Noguchi

21. P-Pwt #12

Optimal Scheduling of Hybrid Renewable Generation System Using Mix Integer Linear

Programming

104

Winasis, Sarjiya, and T Haryono

22. P-TEIa #11

Design and Implementation Human Machine Interface for Remote Monitoring of SCADA

Connected Low-Cost Microhydro Power Plant

109

Alief Rakhman Mukhtar, Suharyanto, and Eka Firmansyah

23. P-TEIa #12

Equivalent Salt Deposit Density and Flashover Voltage of Epoxy Polysiloxane Polymeric

Insulator Material with Rice Husk Ash Filler in Tropical Climate Area

113

Arif Jaya, Tumiran, Hamzah Berahim, and Rochmadi

24. P-TEIa #13

Tracking Index of Epoxy Resin Insulator 119

Abdul Syakur, Tumiran, Hamzah Berahim, and Rochmadi

25. S-IND #11

Semiconducting CNTFET Based Half Adder/Subtractor Using Reversible Gates 124

V.Saravanan, and V.Kannan

26. S-MAS #11

Preliminary Design for Teleoperation Systems under Nonholonomic Constraints 129

Adha I. Cahyadi, Rubiyah Yusof, Bambang Sutopo, Marzuki Khalid, and Yoshio

Yamamoto

27. S-Jkrt #11

PACS Performance Analysis In Hospital Radiology Unit 134

Sugeng Riyadi, and Indra Riyanto

28. S-Srby #11

Middleware Framework of AUV using RT-CORBA 141

Nanang Syahroni, and Jae Weon Choi

29. S-Srby #12

Convolute Binary Weighted Based Frontal Face Feature Extraction for Robust Person’s

Identification

147

Bima Sena Bayu D., and Jun Miura

30. S-Srby #13

Evaluation of Speech Recognition Rate on Cochlear Implant 153

Nuryani, and Dhany Arifianto

31. S-Mlng #11

Remote Laboratory Over the Internet for DC Motor Experiment 157

Aryuanto Soetedjo, Yusuf Ismail Nakhoda, and Ibrahim Ashari

32. S-Mlng #12

Comparative Analysis of Neural Fuzzy and PI Controller for Speed Control of Three Phase

Induction Motor

162

Ratna Ika Putri, Mila Fauziyah, and Agus Setiawan

33. S-Bndg #11

Programmable Potentiostat Based ATMEL Microcontroller for Biosensors Application 168

Erry Dwi Kurniawan, and Robeth V. Manurung

34. S-Bndg #12

Dummy State: An Improvement Model for Hybrid System 172

Sumadi, Kuspriyanto, and Iyas Munawar


DEEIT, UGM – IEEE Comp. Soc. Ind. Chapter vii

35. S-Smrg #11

Fuzzy C-Means Algorithm for Adaptive Threshold on Alpha Matting 177

R. Suko Basuki, Moch. Hariadi, and R. Anggi Pramunendar

36. S-Smrg #12

Analysis of Performance Simulator Water Level Control at Fresh Water Tank in PLTU with

Microcontroller

182

M Denny Surindra

37. S-Pwt #11

An FPGA Implementation of Automatic Censoring Algorithms for Radar Target Detection 187

Imron Rosyadi

38. S-Yog #11

On The Influence of Random Seeds Evaluation Range in Generating a Combination of

Backpropagation Neural Networks

195

Linggo Sumarno

39. S-UGM #11

Analisis EEG Menggunakan Transformasi Fourier Waktu-singkat dan Wavelet Kontinu:

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capacity and quality of single cell wimax network for voip .... capacity and...wimax 802.16e-2005 is...

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