Comparison of some algorithms for tap weight evaluation in adaptive echo cancellers

The performance of some adaptive algorithms for coefficient updating of a digital echo canceller are compared. The examined algorithms are the least mean square one (LMS), the normalized LMS and the simplified versions employing the sign information. Their performance are evaluated on the basis of the echo return loss enhancement (ERLE) steady state value and convergence speed. For the algorithms employing a linear function of the error, as gradient estimate, the resuIts show that convergence speed is dependent on the echo canceller tap number and that its trend is exponential. Algorithms employing the error sign as gradient estimate are the slowest if the same variance of residual echo must be obtained. Furthermore some consideration are made in comparison with an algorithm designed in order to minimize the mean square error evaluated over a M sample block.