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In this paper, we present a Bayesian channel estimation algorithm formulticarrier receivers based on pilot symbol observations. The inherent sparsenature of wireless multipath channels is exploited by modeling the priordistribution of multipath components' gains with a hierarchical representationof the Bessel K probability density function; a highly efficient, fastiterative Bayesian inference method is then applied to the proposed model. Theresulting estimator outperforms other state-of-the-art Bayesian andnon-Bayesian estimators, either by yielding lower mean squared estimation erroror by attaining the same accuracy with improved convergence rate, as shown inour numerical evaluation.

A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation