Fast algorithms for identification of rapidly fading channels

The problem of identification/tracking of rapidly fading communication channels is considered. When the channel coefficients vary rapidly with time the most frequently used weighted least squares (WLS) and least mean squares (LMS) algorithms are not capable of tracking the changes satisfactorily. To obtain good estimation results one has to use more specialized adaptive filters, such as the basis function (BF) algorithms which are based on explicit models of parameter changes. Unfortunately, estimators of this kind are numerically very demanding. The paper introduces a new class of recursive algorithms which combine low computational requirements, typical of WLS and LMS filters, with very good tracking capabilities, typical of BF filters.