Abstract—Wireless radio channels cause severe distortion in
the signals. These distortions can be reduced by using different
channel equalization techniques. In this paper, we compare the
equalization performance of state-space recursive least squares
(SSRLS) and state-space recursive least squares with adaptive
memory (SSRLSWAM) to offset the effect of a linear dispersive
channel. These adaptive filters are well-suited for the estimation
of deterministic signals corrupted by the observation noise. We
consider the equalization of both the linear time invariant and
linear time varying systems to compare the performance of
these filters. The performance is affected by the observation
noise variance, choice of the forgetting factor and the model
mismatch. We present simulation results to compare these cases
by tracking a deterministic signal. It has been shown that
SSRLSWAM outperforms SSRLS in both the time invariant
and time varying channels.
Index Terms—SSRLS, SSRLSWAM, adaptive channel
equalization, tracking, radio channels
Muhammad Zeeshan is with the Department of Electrical Engineering,
College of Electrical and Mechanical Engineering, National University of
Sciences and Technology, Pakistan (e-mail:
ranazeeshan@ceme.nust.edu.pk).
Ihsan Ullah is with the Department of Electrical Engineering, Hanyang
University, South Korea (e-mail: engr.ihsan@hotmail.com).
[PDF]
Cite:Muhammad Zeeshan and Ihsan Ullah, "Comparative Analysis of SSRLS and SSRLS with
Adaptive Memory for Wireless Channel Equalization," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 604-607, 2013.
