Title :
Reduced Complexity Belief Propagation Algorithm Based on Iterative Groupwise Multiuser Detection
Author :
Bavarian, Sara ; Cavers, James K.
Author_Institution :
Simon Fraser Univ., Burnaby
Abstract :
We propose a new method to reduce the complexity of belief propagation algorithm (BP) using an iterative groupwise multiuser detection approach. Replacing the optimal joint maximum a posteriori (JMAP) detectors in BP function nodes by the iterative multiuser detection algorithm (IMUD) reduces the computational load of BP. We explain why IMUD is a good choice for this task and investigate the performance of this reduced complexity BP via simulation.
Keywords :
belief maintenance; computational complexity; iterative methods; belief propagation algorithm; iterative groupwise multiuser detection; iterative multiuser detection algorithm; Belief propagation; Computational complexity; Computational modeling; Detectors; Frequency; Graphical models; Iterative algorithms; Iterative methods; Multiuser detection; Parity check codes;
Conference_Titel :
Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
1-4244-1020-7
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2007.123
