Iterative Multiuser Detection based on Monte Carlo Probabilistic Data Association
Date
2005
Authors
Shi, Zhenning
Reed, Mark
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Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
Multiple-Access Interference (MAI) has been considered as a major performance-limiting factor in the next-generation CDMA systems. Multiuser detection (MUD) methods have been proposed to mitigate the MAI from the co-channel users by incoporating the cross-correlation properties between users. Recently, two classes of emerging techniques, probabilistic data association (PDA) and Markov Chain Monte Carlo (MCMC) methods, have been applied to the multiuser detection. In this paper, we present a new method, named Monte Carlo PDA (MC-PDA), that incorporates the concepts of both to give a more reliable inference of the CDMA symbols by appropriately modelling and updating the MAI. The methodology is general and can be applied to other communication channels.
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Keywords
Keywords: Correlation properties; Markov Chain Monte Carlo (MCMC) methods; Multiple-Access Interference (MAI); Code division multiple access; Codes (symbols); Computer simulation; Iterative methods; Markov processes; Probabilistic logics; Monte Carlo methods
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Source
Proceedings of the 2005 IEEE International Symposium on Information Theory
Type
Conference paper
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Restricted until
2037-12-31
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