Efficient Noise Cancellation Systems Based on Adaptive Algorithms and Their Performance Comparisons

Noise cancellation systems with improved performance and low computational costs are presented in this paper. In speech applications, slow convergence and high computational burden are the main problems incorporating with conventional noise and echo cancellation method. Numerous algorithms have been formulated to overcome these problems. In this paper a comparison is made between LMS, NLMS and RLS algorithms. The analysis shows that NLMS algorithm performs well in case of convergence as well as in terms of Mean Square Error (MSE). Here the adaptive algorithms are implemented using MATLAB. I INTRODUCTION Mobile telephones are often used in a noisy and reverberant environment. When such a device is used in hands-free mode the distance between the desired speaker and the microphone is usually larger than the distance encountered in handset mode. Therefore, the received microphone signal is degraded by the acoustic echo of the far-end speaker, room reverberation and background noise. The acoustic echo cancellation problem is usually solved by using an adaptive filter in parallel to the acoustic echo path. The adaptive filter is used to generate a signal that is a replica of the acoustic echo signal. An estimate of the near-end speech signal is then obtained by subtracting the estimated acoustic echo signal, i.e., the output of the adaptive filter, from the microphone signal. In practice there is always residual echo, i.e., echo that is not suppressed by the echo cancellation system. The residual echo results from the deficient length of the adaptive filter, the mismatch between the true and the estimated echo path, and nonlinear signal components.