Abstract

We present a new subband affine projection (SAP) algorithm for the adaptive acoustic echo cancellation with long echo path delay. Generally, the acoustic echo canceller suffers from the long echo path and large computational complexity. To solve this problem, the proposed algorithm combines merits of the affine projection (AP) algorithm and the subband filtering. Convergence speed of the proposed algorithm is improved by the signal-decorrelating property of the orthogonal subband filtering and the weight updating with the prewhitened input signal of the AP algorithm. Moreover, in the proposed algorithms, as applying the polyphase decomposition, the noble identity, and the critical decimation to subband the adaptive filter, the sufficiently decomposed SAP updates the weights of adaptive subfilters without a matrix inversion. Therefore, computational complexity of the proposed method is considerably reduced. In the SAP, the derived weight updating formula for the subband adaptive filter has a simple form as ever compared with the normalized least-mean-square (NLMS) algorithm. The efficiency of the proposed algorithm for the colored signal and speech signal was evaluated experimentally.

Highlights

  • Adaptive filtering is essential for acoustic echo cancellation

  • A large computational complexity is a major drawback for its implementation, because P-ordered affine projection (AP) adaptive filter is based on the data matrix that consists of the last P + 1 input vectors and it requires matrix inversion in weight updating

  • In subband structure with orthogonal analysis filter banks, the convergence speed of the subband adaptive filter (SAF) is improved by the weight updating with prewhitened inputs that result from the orthogonal subband filtering (OSF)

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Summary

INTRODUCTION

Adaptive filtering is essential for acoustic echo cancellation. Among the adaptive algorithms, least-mean-square (LMS) is the most popular algorithm for its simplicity and stability. When the input signal is highly correlated and the long-length adaptive filter is needed, the convergence speed of the LMS adaptive filter can be deteriorated seriously [1, 2] To overcome this problem, the affine projection (AP) algorithm was proposed [3,4,5,6,7,8,9,10,11]. In subband structure with orthogonal analysis filter banks, the convergence speed of the subband adaptive filter (SAF) is improved by the weight updating with prewhitened inputs that result from the OSF. We present a new subband affine projection (SAP) algorithm to improve convergence speed and reduce computational complexity of the AP algorithm.

AFFINE PROJECTION ALGORITHM
SUBBAND AFFINE PROJECTION ALGORITHM
Extension to the M-subband case
The projection order reduced by signal partitioning
Convergence of the mean weight vector
Computational complexity
SIMULATION RESULTS
The proposed SAP with real speech input
MSE performance of the SAP and the simplified SAP
CONCLUSIONS
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