Title :
Comments on Why Generalized BP Serves So Remarkably in 2-D Channels
Author :
Shental, Ori ; Shental, Noam ; Shamai, Shlomo ; Kanter, Ido ; Weiss, Anthony J. ; Weiss, Yair
Author_Institution :
Univ. of California, San Diego
fDate :
Jan. 29 2007-Feb. 2 2007
Abstract :
Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.
Keywords :
Gaussian channels; belief networks; channel estimation; 2D Gaussian channels; GBP algorithm; Shannon-theoretic information rates; a-posteriori probabilities; generalized belief propagation algorithm; AWGN; Belief propagation; Gaussian channels; Graphical models; Information rates; Interference; Message passing; Nearest neighbor searches; Probability; Two dimensional displays;
Conference_Titel :
Information Theory and Applications Workshop, 2007
Conference_Location :
La Jolla, CA
Print_ISBN :
978-0-615-15314-8
DOI :
10.1109/ITA.2007.4357604
