Markov Chain Monte Carlo MIMO Detection Methods for High Signal-to-Noise Ratio Regimes

Markov Chain Monte Carlo methods have recently been applied as front-end detectors in multiple- input multiple-output (MIMO) communication systems. Moreover, the near capacity behavior of such detectors in low signal-to-noise ratio (SNR) regimes have been demonstrated through computer simulations. However, it has also been found that the MCMC MIMO detectors degrade in high SNR regimes. This paper investigates into the source of this degradation and proposes a number of ad hoc methods to resolve this undesirable behavior of the MCMC MIMO detectors. The effectiveness of the proposed methods is shown through empirical (simulation) results.