A novel variable step size adjustment method based on channel output autocorrelation for the LMS training algorithm

A novel variable step size least mean squares (VSS-LMS) algorithm based on channel output autocorrelation has been proposed to improve the weakness of previous VSS-LMS for application to unknown channel estimation or system identification in low-SNR in this paper. Computer simulations have been performed to show the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed VSS-LMS algorithm has considerably better performance than conventional LMS, RLS, normalized LMS (N-LMS) and the other VSS-LMS algorithms.

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