Estimation of Multipath Channels With Long Impulse Response at Low SNR via an MCMC Method

摘要

This paper addresses the estimation of multipath channels with long impulse response at low signal-to-noise ratio (SNR). The channel sparseness impulse response is modeled by means of a Bernoulli-Gaussian process. Then, the optimization of the resulting posterior distribution resorts to Monte Carlo Markov chain (MCMC) simulation techniques. Special attention is devoted to noise correlation involved by matched filtering: Taking this correlation into account in the algorithm derivation leads to significantly improved performance for both amplitude and time-delay estimation. The method is also extended to cope with Doppler frequency offsets. In particular, simultaneous paths with different Doppler offsets can be estimated. Crameacuter-Rao lower bounds (CRLBs) are derived and presented together with simulation results