A COMPARISION OF PERFORMANCE OF MVSSA WITH OTHER CONVENTIONAL ADAPTIVE ALGORITHM FOR ECHO CANCELLATION
Gunjan Kohar and Vikas Mittal
Prof. in ECE department MMEC, Mullana. Email: firstname.lastname@example.org , email@example.com
Acoustic Echo Cancellation is a common occurrence in todays telecommunication systems. The signal interference caused by acoustic echo is distracting to users and causes a reduction in the quality of the communication. Echo cancellers are very successful and today almost no echo at all can be perceived while using telephones. The Normalized Least Mean Square Algorithm (NLMS) is always the favorable choice because of fast convergence speed. NLMS has higher ERLE so it works as a better algorithm for Echo Cancellation application. The performance of NLMS is better as compared to that of LMS, VSS LMS. The present work focus on the conventional adaptive algorithms and Modified Variable Step Size LMS algorithm to reduce the unwanted echo. A Variable Step Size Least Mean Square (VSS LMS) Algorithm is given with significant changes in which scalar step size increases or decreases as the squared error increases or decreases, thereby allowing the adaptive filter to track changes in the system and produces a smaller steady state error. A new VSS LMS algorithm is proposed, which can effectively adjust the step size while maintain the immunity against independent noise disturbance. The Modified VSS LMS algorithm allows more flexible control of misadjustment and convergence time without the need to compromise one for the other. Simulation results are presented to support the analysis and to compare the performance of the modified algorithm with the other conventional adaptive algorithms. They show that the MVSS algorithm provides faster speed of convergence among other Variable Step Size algorithms while retaining the same small level of misadjustment and the mean square error. An attempt has been made to examine adaptive filtering techniques as they applied to acoustic echo cancellation, to simulate these adaptive filtering algorithms using MATLAB and to compare the performance of these adaptive filtering algorithms as they applied to the acoustic echo cancellation application.
Index Terms: Acoustic Echo cancellation (AEC), LMS, NLMS, VSS LMS.
eJournal of Mathematical Sciences, Technology and Humanities
Issue 2, Pages: 1026 - 1031