Abstract
This paper presents a mean square error (MSE) analysis of the recursive least square (RLS) algorithm for system identification over wide-sense stationary uncorrelated scattering (WSSUS) fading channels. A new sum-of-sinusoids (SOS) model for modeling fading channel is proposed. Unlike most of RLS analyses, our analysis takes the correlation of the inverse of correlation matrix into account and hence yields an improved recursive formula for the MSE, which can be computed recursively with the information of the second order statistics of fading channels. The steady state MSE of RLS is derived for Clarke's model. It is shown that the MSE analysis using the SOS model have much better agreement with experimental results than the AR model.
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