International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 9 - Issue 10, October 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Performance Analysis Of LMS Channel Equalizer For Sinc Pulse And Rectangular Pulse Low Pass Channels

[Full Text]



Saurabh Shah, Ved Vyas Dwivedi, Jaymin Bhalani



Channel Equalization, Eye Diagram, ISI, LMS Equalizer, Mean Square Error, weight adaption, Step size delta.



In Digital Communication System, the requirement of high-speed data transmission achieved through the channel is most important. But in transmission, the data flow rate is reduced due to the Inter Symbol Interference (ISI). For removing this ISI, we require a Channel equalizer. In this paper, we used the Least Mean Square (LMS) equalizer technique. LMS technique shows the convergence of weights with sampling instant and also compare the eye diagram before and after the adaptive equalizer. The adaptive LMS equalizer reduced the ISI and gives better performance.



[1] J. G. Proakis, Digital Communication, McGraw Hill, New York, 2001.
[2] S. Haykins, Analog and Digital Communications, Prentice Hall, 1996.
[3] Jagyanseni Sahoo, Laxmi Prasad Mishra, Sarthak Panda, Mihir Narayan Mohanty “Channel Equalization Using Adaptive Zero Forcing Technique in Rayleigh Fading Channel” International Conference on Information Technology, pp 60-64, IEEE 2015.
[4] Harmandeep Singh, S.S. Gill, “Approaches to Channel Equalization” International Conference on Advanced Computing & Communication Technologies, pp 172-175, IEEE Computer society, 2012.
[5] Nisha Wadhwa, Savita Rangi, Dheeraj Rathee, “Intersymbol Interference Reduction and Bit Error Rate Reduction in Wireless Channels Using Zero Forcing Equalizer”, IOSR Journal of Electronics and Communication Engineering, Volume 9, Issue 3, Ver. III, PP 82-85, May - Jun. 2014.
[6] Linghui Wang, Wei He, Kaihong Zhou, and Zhen Huang, “Adaptive Channel Equalization based on RLS Algorithm”, International Conference on System Science, Engineering Design and Manufacturing Informatization, pp 105-108, IEEE conference 2011.
[7] S. U. H. Qureshi, “Adaptive Equalization,” IEEE, vol. 73, pp. 1349–1387, September 1985.
[8] Michael Tüchler, Andrew C. Singer, and Ralf Koetter, “Minimum Mean Squared Error Equalization Using A Priori Information”, IEEE Transactions on Signal Processing, Vol. 50, No. 3, March 2002.