Performance of GA and PSO aided SDMA/OFDM Over-Loaded System in a Near-Realistic Fading Environment

K. V. Shahnaz, C. K. Ali

Department of Electronics and Communication Engineering, National Institute of Technology Calicut, Kozhikode, India.

DOI: 10.4236/wet.2012.34031                

Abstract

In this work, two popular evolutionary algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) based SDMA-OFDM multi user detection (MUD) have been presented which overcome the limitations of classical detectors. They are simple to implement and their complexity in terms of decision-metric evaluations is very less compared to maximum likelihood detection (MLD). These techniques are shown to provide a high performance as compared to the other detectors especially in a rank-deficient scenario where numbers of users are high as compared to the base station (BS) antennas. In this scenario, Zero forcing (ZF) and minimum mean square error (MMSE) based MUDs exhibit severe performance degradation. To investigate almost realistic performance of a wireless communication system, it is important to use a proper channel model. Since the simulation parameters in this work are based on IEEE 802.11n wireless local area network (WLAN) standard, TGn is the channel model used.

Keywords

Space Division Multiple Access (SDMA); Orthogonal Frequency Division Multiplexing (OFDM); GA; PSO; TGn Channel Model

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	M. Jiang and L. Hanzo, “Multiuser MIMO-OFDM for Next-Generation Wireless Systems,” Proceedings of the IEEE, Vol. 95, No. 7, 2007, pp. 1430-1468.
[2]	L. Hanzo, Y. Akhtman, L. Wang and M. JIANG, “MIMOOFDM for LTE, WiFi and WiMAX,” John Wiley & Sons, Hoboken, 2011.
[3]	R. Prasad, “OFDM for Wireless Communications Systems,” Artech House Publishers, 2004.
[4]	P. Vandenameele, “A Combined OFDM/SDMA Approach,” IEEE Journal on Selected Areas in Communications, Vol. 18, No. 11, 2000, pp. 795-825. doi:10.1109/49.895036
[5]	P. A. Haris, E. Gopinathan and C. K. Ali., “Blind Successive Interference Cancellation for Multi-Carrier CDMA Systems in Indoor Wireless Networks,” WSEAS Transactions on Communications, Vol. 8, 2009, pp. 1192-1203.
[6]	L. Hanzo, M. Munster, B. J. Choi and T. Keller, “OFDM and MC-CDMA for Broadband Multi-User Communications WLANs and Broadcasting,” IEEE Press/Wiley, Piscataway, 2003. doi:10.1002/9780470861813
[7]	V. Erceg et al., “IEEE 802.11 Wireless LANs: TGn Channel Models,” 2004.
[8]	R. L. Haupt and S. E. Haupt, “Practical Genetic Algorithms,” John Wiley and Sons, New York, 2004.
[9]	J. Kennedy and R. C. Eberhart, “Particle Swarm Optimization,” Proceedings of International Conference on Neural Networks, Perth, 27 November-1 December 1995, pp. 1942-1948.
[10]	B. K. Praveen and S. Das, “Neural Network Based Multiuser Detection Techniques in SDMA-OFDM System,” Proceedings of Annual IEEE India Conference, Hyderabad, 16-18 December 2011, pp. 1-4. doi:10.1109/INDCON.2011.6139436