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The task of CDMA multiuser detection is to simultaneously estimate binarysymbols of $K$ synchronous users from the received $N$ base-band CDMA signals.Mathematically, this can be formulated as an inference problem on a completebipartite graph. In the research on graphically represented statistical models,it is known that the belief propagation (BP) can exactly perform the inferencein a polynomial time scale of the system size when the graph is free fromcycles in spite that the necessary computation for general graphs exponentiallyexplodes in the worst case. In addition, recent several researches revealedthat the BP can also serve as an excellent approximation algorithm even if thegraph has cycles as far as they are relatively long. However, as there exitmany short cycles in a complete bipartite graph, one might suspect that the BPwould not provide a good performance when employed for the multiuser detection.  The purpose of this paper is to make an objection to such suspicion. Morespecifically, we will show that appropriate employment of the central limittheorem and the law of large numbers to BP, which is one of the standardtechniques in statistical mechanics, makes it possible to develop a novelmultiuser detection algorithm the convergence property of which is considerablybetter than that of the conventional multistage detection without increasingthe computational cost significantly. Furthermore, we will also provide ascheme to analyse the dynamics of the proposed algorithm, which can benaturally linked to the equilibrium analysis recently presented by Tanaka.Comment: Submitted to 2003 IEEE International Symposium on Information Theor

A statistical mechanical approach to cdma multiuser detection: propagating beliefs in a dense graph