A generalized probabilistic data association multiuser detector

We present in this paper a general framework for the probabilistic data association multiuser detector (PDAD). This generalization allows for different algorithm variations though the design of interference cancellation (IC) filters. We examine two possible variations. In the first variation, we demonstrate a computational more efficient algorithm than the original PDAD. In the second variation, we draw the connection between the PDAD and some popular soft IC detectors and this connection implies that further performance improvement over the soft IC detectors is possible in a turbo multiuser detection (MUD) by the PDAD. Moreover, we show the equivalence of the two variations, which suggests that the IC step is computationally redundant for both the second variation and the soft IC detectors.