Recursive Bayesian Filtering for Iterative Multiuser Decoding

Abstract: One powerful approach for multiuser decoding is to iterate between a linear multiuser filter (which ignores coding constraints) and individual decoders (which ignore multiple-access interference). Subject to clearly formulated statistical assumptions, a new recursive filter is derived based on the received signal and all the successive estimates provided by the outer decoders over all previous iterations. This approach is motivated by the recent observation that these estimates are loosely correlated during initial iterations. Numerical results show that iterative decoding using this filter provides better performance in terms of the supportable load and convergence speed as compared to previously suggested linear filter based iterative decoders.