Estimation of time-varying frequency-selective channels using a matching pursuit technique

Estimation of fast fading channels with large possible delay spread is considered. The time-varying fading channel taps are explicitly modeled by polynomial basis functions, and the basis coefficients are obtained via a matching pursuit (MP) algorithm. It is shown that, in the case of sparse channels, this approach outperforms the conventional least squares (LS) estimation with polynomial basis functions as well as the conventional adaptive matching pursuit, while still providing significant savings in complexity. Moreover, the MP is used to identify the appropriate polynomial model orders for channel taps that vary at different rates. A new least squares algorithm using matching pursuit (LSMP) is proposed. It is shown that the LSMP performs well for both sparse and non-sparse time-varying channels.