Recursive total least squares algorithm for single-user blind channel equalisation

The problem of blind channel identification/equalisation using second-order statistics or equivalent deterministic properties of the oversampled chann el output has attracted considerable attention. Deterministic blind subspac e algorithms are particularly attractive because of their finite sample con vergence property and because their solution can be obtained in closed form . Most subspace algorithms developed up until now, however, are based on bl ock processing and have high computational and memory requirements. In the payer, adaptive techniques are used to lower the computational burden. A si ngle-user direct symbol estimation algorithm is presented. The first step i n the algorithm consists of an adaptive matrix singular value decomposition for a (virtual) channel identification-type operation. A recursive total l east squares algorithm is then used to recover the input symbols. The algor ithm is able to track time-varying channels.