Performance of noise canceller using adjusted step size LMS algorithm

An adjusted step size LMS (least mean squares) algorithm is proposed for possible improvements in the performance of adaptive FIR filters in nonstationary environments. Nonstationary signals means that the statistical properties of the noise changes in time such as the high frequency channel time variations. In the paper, an adaptive noise canceller is proposed which is based on signal to noise ratio number to adjust the step size. In addition the same algorithm can be used for line enhancement and tracking high frequency channels which is used to provide high data rate in communications.