Bp, Mf, And Ep For Joint Channel Estimation And Detection Of Mimo-Ofdm Signals

2016 IEEE Global Communications Conference (GLOBECOM)(2016)

引用 5|浏览9
Receiver algorithms which combine belief propagation (BP) with the mean field (MF) approximation are well-suited for inference of both continuous and discrete random variables. In wireless scenarios involving detection of multiple signals, the standard construction of the combined BP-MF framework includes the equalization or multi-user detection functions within the MF subgraph. However, the MF approximation is not particularly effective for multi-signal detection. For this reason, we propose a new factor graph construction for application of the BP-MF framework to problems involving the detection of multiple signals. We also developed a low-complexity variation to the proposed construction in which Gaussian BP is applied to detection and expectation propagation links the discrete BP and Gaussian BP subgraphs. The result is a probabilistic receiver architecture with strong theoretical justification which can be applied to multi-signal detection and, in general, detection in the presence of interference.
joint channel estimation,MIMO-OFDM signal detection,receiver algorithm,belief propagation,mean field approximation,multi-user detection functions,Gaussian BP subgraphs,discrete BP subgraphs,expectation propagation links,MF subgraph,EP
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