Multiuser detection based on reduced complexity probabilistic data association

We consider a multiuser detector based on modelling the multiple-access interference (MAI) as a vector of Gaussian random variables. This approach leads to the probabilistic data association (PDA) multiuser detector, which outputs good approximations to marginal posterior-mode optimal decisions. A simplification to the PDA detector is suggested, leading to a soft interference cancellation scheme. In the large system limit, the bit error rate performance of this detector can be accurately predicted, and shown to be identical to the optimal detector.