International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Comparative Study of Adaptive Filter Algorithm of a QO-STBC Encoded MIMO CDMA System

Author NameAuthor Details

Shohidul Islam, Husnul Ajra

Shohidul Islam[1]

Husnul Ajra[2]

[1]World University of Bangladesh, Dhaka, Bangladesh.

[2]Hamdard University Bangladesh, Dhaka, Bangladesh.

Abstract

This paper represents a comparative Study of filter algorithms Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) by considering a Quasi Orthogonal Space Time Block Code (QO-STBC) encoded Multiple Input Multiple output (MIMO) Code Division Multiple Access (CDMA) system. MIMO-CDMA system has been currently acknowledged as one of the most competitive technology. Here, the adaptive behaviors of the algorithm are studied. Implementation aspects of these algorithms are their computational complexity and Signal to Noise ratio which are also examined. Recently adaptive filtering algorithms have a nice tradeoff between the complexity and the convergence rate. In this system, by comparative study of three adaptive filter algorithms, the RLS algorithm has faster convergence rate than LMS and NLMS algorithms with better robustness to unpredictable situation and better tracking capability.

Index Terms

Adaptive filter

Least Mean Square (LMS)

Normalized Least Mean Square (NLMS)

Recursive Least Square (RLS)

and Multiple Input Multiple output (MIMO) Code Division Multiple Access (CDMA)

Reference

  1. 1.
    L. Kansal, A. Kansal, K. Singh, “Perfomance Analysis of MIMO-OFDM System Using QOSTBC Code Structure for M-QAM,” in Canadian Journal on Signal Processing, vol.2(2), 2011, pp.4-14.
  2. 2.
    H. Jiang, P. Wilford, “A hierarchical modulation for upgrading digital broadcast systems,” in IEEE Transactions on Broadcasting, vol.51(2), ,2005, pp.223-229.
  3. 3.
    Q. Qu, L.B. Milstein, D.R.Vaman, “Cognitive Radio Based Multi-User Resource Allocation in Mobile Ad Hoc Networks Using Multi-Carrier CDMA Modulation,” in IEEE Journal on Communications, vol.26(1), 2008, pp.70-82.
  4. 4.
    T. S. “Rappaport. Wireless Communications: Principles and Practice,” in 2nd Edition, Prentice Hall, 2002, pp.1-22.
  5. 5.
    A Pandey, L.D. Malviya, V. Sharma, “Comparative Study of LMS and NLMS Algorithms in Adaptive Equalizer,” in International Journal of Engineering Research and Applications,vol.2(3),2012, pp.1584-1587.
  6. 6.
    H. Ajra, J. Hasan, M. S. Islam, “BER Analysis of Various Channel Equalization Schemes of a QO-STBC Encoded OFDM based MIMO CDMA System,” in International Journal of Computer Network and Information Security(IJCNIS),vol.6(3), 2014, pp.30-36.
  7. 7.
    A. J. Paulraj, D. A. GORE, R. U. Nabar, H. Bolcskei, “An overview of MIMO communications - a key to gigabit wireless,” in Proceedings of the IEEE,vol.26(1), 2004, ppt.198-218.
  8. 8.
    T. M. Ma, Y. S. Shi, Y. G. Wang, “A Low Complexity MMSE For OFDM Systems Over Frequency Selective Fading Channels,” in EEE Communications Letters, vol.16(3), 2012, pp.304-306.
  9. 9.
    M. X. Ting, Z. M. Yu, T. Y. Bing, T. X. Feng, “DSP Design of Channel Estimation in MIMO-OFDM System,” in Vehicular Technology Conference 66th, IEEE, Baltimore, MD, 2007, pp.1278-1282.
  10. 10.
    H. Ajra, “Performance Evaluation of a QO-STBC Encoded OFDM Based MIMO CDMA Wireless Communication system with various Channel Equalization Schemes,” in Rajshahi University,M.Sc Thesis, 2010, pp.37-80.
  11. 11.
    A. H. Sayed, “Adaptive Filters,” in John Wiley & Sons, Inc, 2008, pp.20-55.
  12. 12.
    M. S. V. Charhate, L. D. Malviya, S. K. Suman, “Performance Comparison of LMS, NLMS and RLS Algorithms for Adaptive Equalizer,” in International Journal of Advanced Electronics & Communication Systems, vol.1(1), 2012, pp.1-4.
  13. 13.
    J. P. Vijay, N. K. Sharma, “Performance Analysis of RLS over LMS Algorithm for MSE In Adaptive Filters,” in International Journal of Technology Enhancements and Emerging Engineering Research, vol.2(4), 2014, pp.40-44.
  14. 14.
    R. K. THENUA, S.K. AGARWAL, “SIMULATION AND PERFORMANCE ANALYSIS OF ADAPTIVE FILTER IN NOISE CANCELATION,” in International Journal of Engineering Science and Technology, vol.2(9), 2010, pp. 4373-4378.
  15. 15.
    J. DHIMAN, SHADAB, K. GULIA, “Comparison between Adaptive filter Algorithms (LMS, NLMS and RLS),” in International Journal of Science, Engineering and Technology Research, vol.2(5), 2013, pp.1100-1103.
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