Nonlinear acoustic echo cancellation based on higher order correlation

In order to compensate the nonlinearly distorted echo in hands-free telephone, a memoryless power-series polynomial nonlinear acoustic echo canceller (AEC) can be used. Conventional nonlinear AEC employs a NLMS adaptive algorithm which can fail to converge in case of double talk or a very noisy environment. In this paper we propose a higher order correlation algorithm using a white Gaussian training signal. With comparable complexity as NLMS, it is most effective at small SNR. Computer simulations demonstrate that the proposed algorithm has a smaller steady-state echo and it is also very robust to background noise.