Iterative Multiuser Detection based on Monte Carlo Probabilistic Data Association
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...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 2005 IEEE International Symposium on Information Theory|
|01_Shi_Iterative_Multiuser_Detection_2005.pdf||133.92 kB||Adobe PDF||Request a copy|
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