DocumentCode
2810079
Title
Reduced Complexity Belief Propagation Algorithm Based on Iterative Groupwise Multiuser Detection
Author
Bavarian, Sara ; Cavers, James K.
Author_Institution
Simon Fraser Univ., Burnaby
fYear
2007
fDate
22-26 April 2007
Firstpage
466
Lastpage
468
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Conference_Location
Vancouver, BC
ISSN
0840-7789
Print_ISBN
1-4244-1020-7
Electronic_ISBN
0840-7789
Type
conf
DOI
10.1109/CCECE.2007.123
Filename
4232782
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