Detection guided LMS estimation of sparse channels

We consider the LMS estimation of a channel which may be well approximated by an FIR model with sparsely separated active or nonzero taps. Such channels are common within telecommunication systems. We propose an active tap detection procedure to exploit this sparse structure and, subsequently, provide greatly enhanced LMS estimation. Unlike other previously proposed detection methods, our method is structurally consistent for both white and coloured input signals