Abstract: In multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, the Bayesian multiuser detection scheme based on the Markov chain Monte Carlo (MCMC) method has good performance in suppressing multipath fading, carrier frequency offset and phase noise. The algorithm, however, cannot find its application in real-time due to a low convergence rate. To solve this problem, we propose a new method called dynamic MCMC detection. Correlation between samples of the system state and the threshold decided on convergence are used to dynamically select the convergence region about the samples of the system state in an iterative operation. This improves capability of real time operations and maintains the performance of the algorithm. Simulation results show that the proposed method has a higher convergence rate and lower bit error rate.

Key words:  Markov chain Monte Carlo （MCMC）, Bayesian algorithm, convergence rate