Mobile WiMAX Physical Layer Optimization and Performance Analysis Towards Sustainability and Ubiquity

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1 Mobile WiMAX Physical Layer Optimization and Performance Analysis Towards Sustainability and Ubiquity Sajal Saha, Angana Chakraborty, Asish K. Mukhopadhyay and Anup Kumar Bhattacharjee Abstract Mobile WiMAX is emerging as a means for low cost reliable wireless broadband connection compared to traditional DSL cable. The system requirement of next generation mobile WiMAX is supposed to be based on IEEE m which is still in letter ballot stage. This paper attempts to make in depth performance evaluation of Mobile WiMAX under various PHY parameters such as modulation and coding schemes (MCS), cyclic prefixes and different path-loss models. Moreover it also present an optimized adaptive modulation scheme that senses the SNR and adaptively switches to required MCS towards achieving the desired level of Quality of Service (QoS) and link stability. Simulation results show that dynamic adaptation of modulation and coding scheme based channel conditions can offer enhanced throughput, load, reduced delay, SNR and BER. Keywords Wimax Path-loss Modulation and coding Load Throughput 1 Introduction The demand for connectivity and bandwidth is increasing day by day. LTE and WiMAX emerge as promising technology in the market to meet the requirement of the user in a ubiquitous environment. WiMAX became popular worldwide among S. Saha (&) Narula Institute of Technology, 81, Nilgunj Road, Kolkata , India sajalkrsaha@ieee.org A. Chakraborty Indian Institute of Engineering Science and Technology (IIEST), Howrah , India angana.chakraborty9@gmail.com A.K. Mukhopadhyay SR Group of Institution, Jhansi, India askm55@gmail.com A.K. Bhattacharjee National Institute of Technology, Durgapur, India anupkumar.bhattacharaya@ece.nitdgp.ac.in Springer India 2015 J.K. Mandal et al. (eds.), Information Systems Design and Intelligent Applications, Advances in Intelligent Systems and Computing 339, DOI / _11 101

2 102 S. Saha et al. them due to simplicity of installation and cost reduction compared with traditional DSL cable. There are currently three WiMAX systems available Fixed WiMAX(IEEE ) Mobile WiMAX(IEEE e-2005) Mesh WiMAX(IEEE Mesh) Fixed WiMAX system having coverage area 5 7 km and speed up to 48 Mbps (fixed downlink) and 7 Mbps (fixed uplink). Mobile WiMAX provides speed upto 9.4 Mbps for downlink and 3.3 Mbps for uplink across the coverage area of 3 km. In Mesh WiMAX network WiMAX BS is connected within its coverage area with additional BS with smaller coverage area to relay the connectivity. In this paper various MAC, PHY system design parameters were identified, reviewed and selected on the basis of potential contribution to maximizing performance and minimizing delay and path loss. We identified performance matrices including VoIP packet delay, data packet delay, load, throughput to quantify performances over the optimized mobile WiMAX infrastructure. OPNET modeler and MATLAB are used for simulation. Simulation scenarios were used to observe the impact on the four performance matrices. 2 Background Study In Wireless communication information propagates from transmitted to receiving antenna. During transmission electromagnetic wave faces obstacle causes path loss. Path loss is defined by PL ¼ P T þ G T þ G R P R L T L R where P T and P R are transmitted and received power. G T and G R are the gain of transmitting and receiving antenna. L T and L R are the feeder losses of the respective antennas. Milanovic et al. [1] compared the accuracy of four different propagation models like SUI model, COST 231 Hata, Macro Model, Model With received power for 3.5 GHz analysis is made for location with NLOS and LOS propagation conditions separately. Erceg et al. [2] developed a statistical path loss model derived from 1.9 GHz experimental data collected across suburban environments. In [3] a cross layer architecture is developed considering a adaptive MCS scheme in the PHY and a signal and interference to noise ratio (SINR) based call admission control (CAC) scheme is developed in the MAC layer of the WIMAX architecture. Bhunia et al. [4] considered load, jitter, throughput as QoS parameters to analyze the performance of VoIP application in mobile WiMAX. Nevertheless, we made an in depth analysis of the effect of various pathloss models, scheduling algorithm and MCS scheme. It has been shown that AMC scheme enables better QoS while consuming low overall bandwidth of the system.

3 Mobile WiMAX Physical Layer Optimization Network and System Model We used OPNET simulator and MATLAB for simulation. Optimized Network Engineering Tool (OPNET) provides a development environment supporting the communication networks. Both behavior and performance of the modeled system can be analyzed through discrete event simulator. OPNET provides graphical editor to enter network model details. It consists four such types of editor names network editor, node editor, process editor and parameterized editor organized in a hierarchical way. We design the optimized network model scenario in OPNET, run the model under different condition, collected data and plot the data in MATLAB. We consider different modulation and coding schemes (MCS) like QPSK1/2, QPSK3/4, 16QAM1/2, 16QAM3/4, 64QAM1/2, 64QAM2/3, 64QAM3/4 as the threshold coverage area of each modulation schemes are different as shown in Fig. 1. Coverage area is determined using the maximum signal to noise ratio (SNR) a MN receive without significant data loss. We introduce an Adaptive Modulation Coding (AMC) that allows the WiMAX system to adjust from higher to lower modulation scheme depending on SNR condition of the radio link. AMC model is discussed elaborately in Sect QAM3/4 64-QAM2/3 16-QAM3/4 16-QAM1/2 QPSK3/4 QPSK1/2 QPSK1/8 Fig. 1 Cell decomposition into region by each modulation

4 104 S. Saha et al. Table 1 Parameter taken Min. MN velocity 60 km/h Max. MN velocity 100 km/h Frequency bandwidth used GHz Channel bandwidth 8.75/10 MHz FFT size 1,024 RF multiple access mode OFDMA Antenna type Omni directional MIMO Matrix 4/4 No. of carrears 2 Transmission power Max. 20 W RCV buffer size 64 kb Antenna gain 23 dbi Base station parameters Maximum number of SS nodes 15 Service class name Gold (rtps) Mac address Auto assigned Maximum power transmission 0.5 W PHY profile wireless OFDMA 20 MHz PHY profile type OFDM Mobile station parameters Handover parameters Maximum sustained traffic rate 4 Mbps Minimum reserved traffic rate 0.5 Mbps OPNET offers four inbuilt path loss model [5] environment like, (i) Free Space model: It hardly used in real time environment as it does not consider the multipath fading effect. (ii) Suburban fixed model: Considering cell with large coverage area and higher antenna height considering MN having low mobility. (iii) Outdoor to indoor pedestrian path loss model: Small cell size with low antenna height. Pedestrians are located in streets, inside buildings. (iv) Vehicular environment: Larger cell size and higher antenna height considering MN having mobility ( kmph). rtps is taken in MAC sub-layer as initial QoS service class to support real time services with variable bit rates. Other important parameters are shown in Table AMC Model The aim of this model is to create a universal machine that can be adapted easily based on MN mobility. Antenna gain of the WiMAX Base Station (BS) is fixed at

5 Mobile WiMAX Physical Layer Optimization 105 Fig. 2 State diagram of AMC model 15 dbi. When signal strength is high, highest modulation scheme is used (64 QAM) to increase the system capacity. As MN moves out to the periphery of the coverage area causes signal strength fading, our system model moves to lower modulation scheme to maintain QoS and link stability. Change of MCS depends on the threshold SNR received by MN that continuously sense SNR and change MCS according to AMC algorithm. Working function of AMC model is shown by the state diagram as shown in Fig. 2. Selection of threshold SNR value is a challenging problem. Two techniques to select the threshold SNR are given in [6]. 4 Simulation Results and Analysis We set up two mobile nodes Mobile_1_1 and Mobile_2_1 under base stations BS_1 and BS_2 respectively. We gradually increase the traffic to 2, 5, 8, 10 and 15 MNs and analyze the performance of the WiMAX network. Figure 3 shows 15 MNs WiMAX network model under 15 BSs. Although WiMAX standards supports large coverage area but in practice, it supports approximately 3 km.

6 106 S. Saha et al. Fig. 3 WiMAX network model considering higher traffic (15 MNs) Figures 4 and 5 show delay performance for different fixed type MCS and AMC. Peak VoIP packet delay of AMC is minimum (0.5 ms) among other MCS. Peak delay in Fig. 4 is 3 ms (64QAM3/4) and in Fig. 5 is 9.2 ms (QPSK1/2) that is much below the threshold level of 150 ms as recommended by ITU-T[11]. Variation of load (packets/sec), throughput and SNR have been implemented in Figs. 6, 7 and 8. Initially, the proposed AMC model adapted to higher modulation Fig. 4 variation of VoIP delay different MCS voice packet delay variation 3 x voice packet delay variation with different modulation techniques QPSK1/2 QPSK3/4 16-QAM1/2 16-QAM3/4 64-QAM1/2 64-QAM2/3 64-QAM3/4 Adaptive Handoff Region 0

7 Mobile WiMAX Physical Layer Optimization 107 Fig. 5 Data packet delay at different at MCS 9.2 x 10-3 delay with different modulation techniques QPSK1/2 9.1 QPSK3/4 16-QAM1/2 16-QAM3/4 delay (sec) QAM1/2 64-QAM2/3 64-QAM3/ Fig. 6 Variation of load (packets/sec) different MCS 400 load(packets/sec) with different modulation techniques QPSK1/2 350 QPSK3/4 16-QAM1/2 16-QAM3/4 load (packets/sec) Handoff Region 64-QAM1/2 64-QAM2/3 64-QAM3/4 Adaptive scheme (64 QAM3/4). As MN moves toward the cell boundary, SNR value decreases (Fig. 8) and as it reaches the threshold SNR value, the coding rate changes according to AMC algorithm and the state machine (Fig. 2) keeps different state of lower coding rate (like QPSK1/2) to maintain the quality of the link connection without increasing the signal power (23 dbi). In this way, the proposed AMC model adopts a suitable MCS dynamically based on SNR value (Fig. 8) and keeps almost constant throughput (Fig. 7). Empirical analysis also shows that proposed AMC model and QPSK1/2 achieves 90 % throughput (marked by 2 lines in Fig. 7) as maximum sustainable traffic rate of the communication link is 4 Mbps. 64QAM2/3 and 64QAM3/4 fail to achieve the minimum benchmark of 60 % throughput.

8 108 S. Saha et al. Fig. 7 Throughput performance analysis at different MCS throughput (bits/sec) x 105 throughput with different modulation techniques Handoff Region QPSK1/2 QPSK3/4 16-QAM1/2 16-QAM3/4 64-QAM1/2 64-QAM2/3 64-QAM3/4 Adaptive 0 90% 60% Fig. 8 Downlink SNR respectively at different MCS downlink SNR(dB) downlink SNR with different modulation techniques QPSK1/2 QPSK3/4 16-QAM1/2 16-QAM3/ Figures 9, 10 and 11 represent the variation of delay, load (packet/sec) and throughput respectively in different propagation models keeping MN speed constant(100 kmph). Delay for the free space model is minimum and pedestrian moving from outdoor to indoor is maximum, this may be due to the radio wave component reflected and diffracted on building reaching the receiving antenna. Load and throughput is maximum for the free-space propagation model whereas pedestrian moving from outdoor to indoor is minimum. Although all path loss models achieve the minimum throughput benchmark (60 %) in the proposed Wi- MAX system except handoff duration as shown in the Fig. 7. As far as 60 % throughput is concerned, the rate is adequate to support applications like VoIP and video transmission.

9 Mobile WiMAX Physical Layer Optimization 109 Fig. 9 Variation of delay at different path loss models 7.7 x delay (sec) free space vehicular suburban fixed outdoor to indoor and pedestrian 7.2 Handoff Region 7.1 Fig. 10 Variation of load at different path loss Models load (packets/sec) Handoff Region free space vehicular suburban outdoor to indoor and pedestrian Fig. 11 Variation of throughput at different path loss models x % throughput (bits/sec) free space vehicular 60% suburban 1 outdoor to indoor and pedestrian Handoff Region 0.5

10 110 S. Saha et al. Figure 9 represents delay variation at various path loss models. Figure 10 represents variation of load at different path loss models. Figure 11 represents throughput variation respectively under various path loss models. 5 Conclusions WiMAX is conveniently deployable due to ease of installation and low cost. It is very important to guarantee QoS to the end users to avail and sustain the diversifying applications of WiMAX. An optimized architecture conforming to the recently standardized IEEE m framework, is needed for integrating both mobility management and QoS to provide broadband service in a ubiquitous environment to end users. In [7], authors analyzed the WiMAX network performance under different service classes in MAC layer. In [8], authors proposed a mobility management model THMIP at network layer to achieve better throughput with minimal handoff latency. In this paper, our analysis on the performance of the WiMAX considered following parameters of the physical layer. (a) Different MCS with constant speed (100 kmph) (b) Different speed with proposed AMC (c) Different path loss models with proposed AMC at a constant speed (90 kmph). Performance matrices considered are delay, load, SNR, throughput. From the empirical studies, it is evident that proposed AMC allows the WiMAX network to yield higher throughput covering longer distance. References 1. Milanovic, J., Rimac-Drlje, S., Bejuk, K.: Comparison of propagation models accuracy for WiMAX on 3.5 GHz, electronics, circuits and systems. In: 14th IEEE International Conference on ICECS 2007, pp , Dec Erceg, V., Greenstein, L.J., Tjandra, S.Y., Parkoff, S.R., Gupta, A., Kulic, B., Julius, A.A., Bianchi, R.: An empirically based path loss model for wireless channels in suburban environments. IEEE J. Sel. Areas Commun. 17(7): (1999) 3. Chowdhury, P., Misra, I.S., Sanyal, S.K.: Cross layer QoS support architecture with integrated CAC and scheduling algorithms for WiMAX BWA Networks. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 3(1), (2012) 4. Bhunia, S., Misra, I.S., Sanyal, S.K., Kundu, A.: Performance study of mobile WiMAX network with changing scenarios under different modulation and coding. Int. J. Commun. Syst. 24(8), (2011) 5. OPNET Technologies Inc: Introduction to WiMAX modeling for network R&D and planning. In: Proceedings of OPNETWORK, Washington, DC, USA (2008) 6. Marabissi, D., Tarchi, D., Fantacci, R., Balleri, F.: Efficient adaptive modulation and coding techniques for WiMAX systems. In: IEEE International conference on Communication (ICC), pp (2008)

11 Mobile WiMAX Physical Layer Optimization Saha, S. et.al.: Performance analysis of service classes for IEEE m QoS optimization. In: Proceedings of the 1st International Conference on Emerging Trends and Applications in Computer Science (ICETACS), pp (2013) 8. Saha, S., et al.: QoS and Mobility management issues on next generation mobile WiMAX networks. In: Santos, R., Licea, V., Edwards-Block A. (eds.) Broadband Wireless Access Networks for 4G: Theory, Application, and Experimentation, pp Information Science Reference, Hershey, PA. doi: / ch016

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