Performance Analysis of Different Adaptive Algorithms for Equalization

  • Priyanka Aggarwal Department of Electronics and Communication Engineering, Graphic Era University, Dehradun, India
  • Subhash Chandra Yadav Department of Electronics and Communication Engineering, Graphic Era University, Dehradun, India
  • Pradeep Juneja Department of Electronics and Communication Engineering, Graphic Era University, Dehradun, India
  • R. G. Varshney Department of Mathematics, Graphic Era University, Dehradun, Uttarakhand, India
Keywords: LMS, NLMS, RLS, Adaptive filtering, Convergence rate

Abstract

The major problems in wireless communication are time dispersion and inter symbol interference. In order to cancel out the effect introduced by the unknown channel and to recover the original signal as from the distorted signal, a channel equalizer is required to compensate the effect of channel distortion, time variation and can adapt it-self to the changes in channel characteristics. The equalizers are expected to have fast convergence rate in communication systems which is difficult to achieve with conventional adaptive algorithms. LMS is widely used because it is simple and robust, but performs poor in terms of convergence rate. NLMS is an improved version of LMS and provides better convergence. RLS exhibit best performance but complex and unstable. In this paper we simulated adaptive algorithms such as LMS, NLMs and RLS algorithms in MATLAB and compared their performance.

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Published
2016-09-22
Section
Articles