An Extrinsic Kalman Filter 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 and the history of input signals provided by the outer decoders over all previous iterations, an extrinsic Kalman filter is suggested. This approach is motivated by the recent observation that decoder outputs 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.