Blind Despreading of Short-Code DS-CDMA Signals with Bayesian Techniques

This paper introduces an algorithm for joint spreading codes and information sequences estimation based on reversible jump Markov chain Monte Carlo (RJMCMC) for direct-sequence code division multiple access (DS-CDMA) signals with low signal-to-noise ratio (SNR) in non-cooperative systems, by analyzing signal model. The proposed algorithm establishes a joint posterior distribution model of signal parameters and user number, and obtains the samples of distribution to be estimated through iterative sampling. The algorithm is able to construct a reversible Markov chain sampler that jumps between parameter subspaces of different dimensionality, so that the posterior distribution of parameters to be estimated is obtained. Simulation results indicate that the proposed algorithm can be applied to low SNR with equal or unequal power and to different user number. Moreover, the estimation performance of this algorithm is a significant improvement of the existing method.