SEQUENTIAL LMS FOR LOW-RESOURCE SUBBAND ADAPTIVE FILTERING: OVERSAMPLED IMPLEMENTATION AND POLYPHASE ANALYSIS (ThuPmOR1)

Author(s) : Hamid Sheikhzadeh (Dspfactory Ltd., Canada) Hamid Reza Abutalebi (Yazd University, Iran) Robert L. Brennan (Dspfactory Ltd., Canada) Kevin R. L. Whyte (Dspfactory Ltd., Canada) Edward Chau (Dspfactory Ltd., Canada)

Abstract : The periodic and sequential partial update normalized LMS (P-NLMS and S-NLMS) algorithms and their variants are often used to reduce the computation cost of NLMS. In this paper, S-NLMS is employed in a low-resource subband adaptive filter implemented on an oversampled DFT filterbank. To analyze the system per-formance, we present a polyphase filterbank model for the P-NLMS and S-NLMS algorithms. It is shown that implicitly both algorithms employ perfect reconstruction delay chain analy-sis/synthesis filterbanks. As a result, the decimation involved in partial filter update does not introduce any steady-state perform-ance degradation. The presented model can be employed to further predict and justify the convergence behavior of the partial update algorithms more accurately. Implementation of the S-NLMS algo-rithm on subband adaptive filters employing oversampled filter-banks is next described. Evaluation of the adaptive system per-formance shows that for stationary inputs, the S-NLMS algorithm (with proper step-size scaling) performs very similarly for moder-ate decimation factors of the S-NLMS.

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