Conjugate gradient techniques for multichannel acoustic echo cancellation

Abstract

Conjugate Gradient (CG) techniques arc suitable for resolution of time-variant system identification problems: adaptive equalization, echo cancellation, active noise cancellation, linear prediction, etc. These systems can be seen as optimization problems and CG techniques can be used to solve them. It has been demonstrated that, in the single-channel case, the conjugate gradient techniques provide a similar solution in terms of convergence rate than those provided by the recursive least square (RI.S) method, involving higher complexity than the least mean square (LMS) but lower than RLS without stability issues. The advantages of these techniques are especially valuable in the case of high complexity and magnitude problems like multi-channel systems. This work develops CG algorithm for the adaptive MIMO (multiple-input and multiple-output) systems and tests it by solving a multichannel acoustic echo cancellation (MARC) problem.