The Effects of Large Interference on the Tracking Capability of Digitally Implemented Echo Cancellers

Adaptive mean-square-tapped-delay-line echo cancellers for voice applications are conventionally designed to stop adjustment during periods of "double-talking", i.e., when a large informationbearing signal is present along with the echo signal to be cancelled. Continuous adaption is, however, desirable in full-duplex, two-wire data transmission where the periods of double-talking are so long that the echo channel may vary. We presume that the tap weights of an echo canceller have converged during a training period free of double talking, and address the problem of subsequent echo-canceller tap adjustment via the estimated-gradient algorithm in the presence of double talking. In the estimated-gradient algorithm the tap increment should be proportional to the product of the residual echo and the tap voltage. However, when double talking occurs the residual echo can only be estimated. For an idealized double-talking model, it is demonstrated, from infinite-precision considerations, that use of the memoryless maximum-likelihood estimate of the residual echo is nearly equivalent to abrupt reduction of the step size of the adjustment algorithm when double-talking begins, and could provide an automatic mechanism for recognizing double-talking. Unfortunately, the response of a digitally implemented canceller to a sharply reduced step size can be a deterioration in performance. In fact, the use of an exceedingly small step size during periods of doubletalking may lead to a cancellation error considerably larger than that predicted by coefficient precision. It is demonstrated how averaging the estimated gradient can significantly decrease the mean-squared tap error during periods of double talking. To a first approximation, the tap-weight error can be reduced by a factor proportional to the averaging interval, with an equivalent decrease in tracking capability.