A new adaptive channel estimation filter based on the variable step-size LMS algorithm is shown to perform close to the optimum Wiener filter without assuming a-priori knowledge of the channel fading rate. It is unlike other fixed characteristics filters such as the equal weight moving average and FIR filters designed using the windowing method. Under a non-stationary Rayleigh fading channel where the fading rate varies, the proposed adaptive filter is also able to track the time-varying channel, achieving better performance than the fixed characteristics filters.
Published in:
Communication Systems, 2002. ICCS 2002. The 8th International Conference on
(Volume:1
)
Date of Conference: 25-28 Nov. 2002