000143075 001__ 143075
000143075 005__ 20180317094233.0
000143075 037__ $$aCONF
000143075 245__ $$aChannel estimation by inference on Gaussian Markov random fields
000143075 336__ $$aConference Papers
000143075 520__ $$aIn 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.
000143075 6531_ $$aMarkov random field
000143075 6531_ $$achannel estimation
000143075 6531_ $$achannel modeling
000143075 6531_ $$agaussian message passing
000143075 700__ $$aRiedl, Thomas Johannes
000143075 700__ $$aChoi, Jun Won
000143075 700__ $$aSinger, Andrew Carl
000143075 7112_ $$aIEEE Asilomar Conference on Signals, Systems and Computers$$cPacific Grove, CA$$dNovember, 2009
000143075 773__ $$tProceedings of the 43rd Annual IEEE Asilomar Conference on Signals, Systems and Computers
000143075 8564_ $$zURL
000143075 8564_ $$s238157$$uhttps://infoscience.epfl.ch/record/143075/files/MRFpaper.pdf$$zn/a
000143075 909CO $$ooai:infoscience.tind.io:143075$$pIC$$pconf
000143075 909C0 $$0252058$$pLTHC$$xU10432
000143075 937__ $$aLTHC-CONF-2010-001
000143075 973__ $$aOTHER$$rREVIEWED$$sACCEPTED
000143075 980__ $$aCONF