Subband Echo Canceler with an Exponentially Weighted Stepsize NLMS Adaptive Filter

This paper proposes a novel adaptive algorithm for an echo canceler. In this algorithm, the number of operations and memory capacity are equivalent to those of the conventional NLMS algorithm but the convergence speed is twice that using the conventional algorithm. This adaptive algorithm is referred to as subband ES (exponentially weighted stepsize). In the algorithm, the frequency bands of the received input signal and echo signal are divided into multiple subbands, and echo is independently canceled in each subband. Each adaptive filter in each subband has independent coefficients with an independent stepsize. The stepsize is time-independent and its weight is exponentially proportional to the change of the impulse response within the frequency region, such as the expected value of the difference between the waveforms of two impulse responses. As a result, the characteristic of the acoustic echo path in each frequency band is analyzed using the adaptive algorithm to improve the convergence characteristic. Using the results of computer simulation and experimental results obtained via an experimental setup with DSP, it is shown that the convergence speed with respect to input voice signal can be about 4 times faster when using echo cancellation based on the new algorithm than in conventional full-band echo cancellation based on the NLMS algorithm.