Sparse Channel Estimation with Zero Tap Detection

Algorithms for the estimation of a channel whose impulse response is characterized by a large number of zero tap coefficients are developed and compared. Estimation is conducted in a two-stage fashion where an estimate of the non-zero taps is followed by channel estimation. Tap detection is transformed into an equivalent on-off keying detection problem. Several tap detection algorithms are investigated which tradeoff between complexity and performance. The proposed methods are compared to an unstructured least squares channel estimate as well as a structured approach based on matching pursuit. Three schemes in particular are developed: a sphere decoder based scheme, a Viterbi algorithm based method and a simpler iterative approach. The latter offers a better tradeoff between estimation accuracy and computational cost. A joint estimation and zero tap detection scheme is also considered. All solutions exhibit a significant gain in terms of mean-squared error and bit error rate over conventional schemes which do not exploit the sparse nature of the channel, as well as the matching pursuit approach which does endeavor to exploit the sparsity