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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 budi_s@mti.ugm.ac.id mita.amakusa@gmail.com sigitbw@ugm.ac.id
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)
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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).
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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.
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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
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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.
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[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.
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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
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Department of Electrical Engineering and Information TechnologyFaculty of Engineering, Gadjah Mada UniversityJalan Grafika no. 2, Kampus UGMYogyakarta, 55281, Indonesia
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PROCEEDINGS OF INTERNATONAL CONFERENCE ON
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Yogyakarta, 12 July 2012
DEPARTMENT OF ELECTRICAL ENGINEERING AND INFORMATION TECHNOLOGY
FACULTY OF ENGINEERING GADJAH MADA UNIVERSITY
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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
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Ridi Ferdiana
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Prapto Nugroho
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Selo Sulistyo
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Adhistya Erna Permanasari
Agus Bejo
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Bambang Sutopo
Bimo Sunarfri Hantono
Bondhan Winduratna
Budi Setiyanto
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Eka Firmansyah
Enas Duhri Kusuma
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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
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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
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CITEE 2012 Yogyakarta, 12 July 2012 ISSN: 2088-6578
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:
Studi Kasus Pengaruh Bacaan al Quran
201
Agfianto Eko Putra, and Putrisia Hendra Ningrum Adiaty
40. C-EGY #11
Interference Mitigation for Self-Organized LTE-Femtocells Network 211
Nancy Diaa El-Din, Karim G. Seddik, Ibrahim A. Ghaleb, and Essam A. Sourour
41. C-Jkrt #11
Dual-Band Antenna Notched Characteristic with Co-Planar Waveguide Fed 216
Rastanto Hadinegoro, Yuli Kurnia Ningsih, and Henry Chandra
42. C-Jkrt #12
Edge – Component Order Connectivity Issue In Designing MIMO Antennas 220
Antonius Suhartomo
43. C-Srby #11
Robust Image Transmission Using Co-operative LDPC Decoding Over AWGN Channels 226
M. Agus Zainuddin, and Yoedy Moegiharto
44. C-Srby #12
Parameter Measurement of Acoustic Propagation in the Shallow Water Environment 231
Tri Budi Santoso, Endang Widjiati, Wirawan, and Gamantyo Hendrantoro
45. C-Bndg #11
Radio Network Planning for DVB-T Repeater System Integrated with Early Warning
System
235
Herry Imanta Sitepu, Dina Angela, Tunggul Arief Nugroho, and Sinung Suakanto
46. C-TEIa #11
Considering Power Consumption of Wireless Stations Based on 802.11 Mode Control 240
Ramadhan Praditya Putra, Sujoko Sumaryono, and Sri Suning Kusumawardani
47. C-TEIb #11
The Design Model of 2.4 GHz Dual Biquad Microstrip Antenna 245
Wahyu Dewanto, Penalar Arif, and HC. Yohannes
48. C-TEIb #12
Voice Service Performance of Broadband Cellular Systems 252
Wahyu Dewanto, and Imam Bagus Santoso
49. C-TEIb #13
Capacity and Quality of Single Cell WiMAX Network for VoIP Application 257
Budi Setiyanto, Esmining Mitarum, and Sigit Basuki Wibowo
Cover CITEE 2012.pdfPage 12: Alignment
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