Channel estimation by inference on Gaussian Markov random fields

In this paper, we discuss a novel method for channel estimation. The approach is based on the idea of modeling the complex channel gains by a Markov random field. This graphical model is used to capture the statistical dependencies between consecutive taps in time and delay. The sum-product algorithm is finally employed to infer a MAP channel estimate from given observations