Channel estimation by inference on Gaussian Markov random fields

Thomas Riedl, Jun Won Choi, Andrew C. Singer · 2009

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.

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