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Reseach Article

Linear Block Equalizers in Rayleigh Fading Channel with Normalized Channel Impulse Response

by Abhishek Kumar, Anoop Tiwari, Ravi Shankar Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 6
Year of Publication: 2014
Authors: Abhishek Kumar, Anoop Tiwari, Ravi Shankar Mishra
10.5120/16220-5667

Abhishek Kumar, Anoop Tiwari, Ravi Shankar Mishra . Linear Block Equalizers in Rayleigh Fading Channel with Normalized Channel Impulse Response. International Journal of Computer Applications. 93, 6 ( May 2014), 21-26. DOI=10.5120/16220-5667

@article{ 10.5120/16220-5667,
author = { Abhishek Kumar, Anoop Tiwari, Ravi Shankar Mishra },
title = { Linear Block Equalizers in Rayleigh Fading Channel with Normalized Channel Impulse Response },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 6 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 21-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number6/16220-5667/ },
doi = { 10.5120/16220-5667 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:15:07.975206+05:30
%A Abhishek Kumar
%A Anoop Tiwari
%A Ravi Shankar Mishra
%T Linear Block Equalizers in Rayleigh Fading Channel with Normalized Channel Impulse Response
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 6
%P 21-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Linear adaptive equalizers are widely used in wireless communication systems in order to reduce the effects of the channel distortion. Various researchers have used linear block equalizers for different modulations techniques. In this paper the BER performance of different M-PSK and M-QAM modulations with the block based LMS and RLS linear equalizers are compared over the flat and frequency selective Rayleigh fading channel. For achieving better performance the Rayleigh channel is modeled with four multipath channels and normalized channel impulse response under the presence of AWGN noise. The maximum Doppler shifts frequencies are varied for evaluating the performance of the equalizers. Using the normalized channel impulse response improves the BER performance of the communication system for the higher values of M as 512 and 1024. Transmitted and received constellation diagrams are also compared for different equalizers. Performance is also compared for the different equalizer weights and block sizes.

References
  1. S C Lin, "Performance analysis of decision feedback equalizer for cellular mobile radio co-channel interference and fading" IET Communicatio Vol. 3, Issue. 1, pp. 100-114 2009,
  2. S. Alireza Banani, Rodney G. Vaughan, "Itterative Blind Linear Equalizer in time varying disapersive channel", 3rd International conf. on Electrical and Computer Engineering (CCECE) pp 1-6 2010.
  3. Xin Wang and Guangzeng Feng. "A constant Modulous algorithm for phase modulation signal", IEEE 7th international Conf. on Networking, pp. 584-587, 2008
  4. Sabita Nahata, 2subrata Bhattacharya, "Comparative analysis of modulation schemes using Adaptive Equalizers as a fading mitigation technique", International Journal of Electronics Signals and Systems, Vol-1 Iss-3, pp. 25-31, 2012
  5. Wing Seng Leon,, Umberto Mengali, "Equalization of Linearly Frequency-Selective Fading Channels", Ieee Transactions On Communications, Vol. 45, No. 12, December 1997
  6. Yu Gong, Xia Hong and Khalid F. Abu-Salim, :" Adaptive MMSE equalizer with optimum Tap length and Decision delay", IEE 2010
  7. F. Riera-Palou, J. M. Noras, and D. G. M. Cruickshank, "Linear equalisers with dynamic and automatic length selection," Electronic Letters, voL 37, no. 25, pp. 1553 - 1554, Dec. 2001
  8. Y. Gu, K. Tang, H. Cui, and W. Du, "LMS algorithm with gradient descent filter length," IEEE Signal Processing letters, voL II, no. 3, pp. 305 - 307, March 2004.
  9. Kiran Kuch, "Limiting Behavior of ZF/MMSE Linear Equalizers in Wideband Channels with Frequency Selective Fading", IEEE Communications Letters, Vol. 16, No. 6, June 2012
  10. X. Ma and W. Zhang, "Fundamental limits of linear equalizers: diversity, capacity, and complexity," IEEE Trans. Inf. Theory, vol. 54, pp. 3442–3456, Aug. 2008.
  11. Jaymin Bhalani, A. I. Trivedi, Y. P. Kosta , "Performance Comparison of Non-Linear and Adaptive Equalization Algorithms for wireless communication channel" IEEE 2009
  12. Fu Shaozhong, Ge Jianhua??Wang Yong, " Fast adaptive algorithm for variable length equalizer based on exponential", Proc. of IEEE International Conferences o Wireless Communication, Networking and Mobile Computing. WiCOM 08, 2008
  13. Veeraruna Kavitha and Vinod Sharma, "Tracking performance of LMS-iinear equalizers for fading channel", Forty-Fourth Annual Allerton Conference Allerton House, UIUC, Illinois, USA, pp. 681-686, Sept 2006.
  14. Garima Malik, Amandeep Singh Sappal, "Adaptive equalization algorithm: An Overview", International Journal of Advanced Computer Science and Applications (IJACSA) Vol. 2, No. 3, March 2011
  15. Wee-Peng Ang, B. Farhang-Boroujeny, "A New Class of Gradient Adaptive Step-Size LMS Algorithms", IEEE Trans. On Signal Processing, Vol. 49, No. 4, April 2001
  16. A. Molisch, "Wireless Communication", E- Book Wiley-IEEE Press in 2011
  17. Suneeta V. Budihal, Priyatamkumar, R. M. Banakar, "Performance analysis of Adaptive Decision Feedback Turbo Equalization (ADFTE) using Recursive Least Square (RLS) Algorithm over Least Mean Square (LMS) Algorithm", IEEE International Conference on Computational Intelligence and Multimedia Applications 2007
Index Terms

Computer Science
Information Sciences

Keywords

Linear Equalizers LMS RLS algorithm Normalized channel impulse response Bit error rate.