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 channel output has attracted considerable attention. Deterministic blind subspace algorithms are particularly attractive because of their finite sample convergence property and because their solution can be obtained in closed form. Most subspace algorithms developed up until now, however, are based on block processing and have high computational and memory requirements. In the paper, adaptive techniques are used to lower the computational burden. A single-user direct symbol estimation algorithm is presented. The first step in the algorithm consists of an adaptive matrix singular value decomposition for a (virtual) channel identification-type operation. A recursive total least squares algorithm is then used to recover the input symbols. The algorithm is able to track time-varying channels