Adaptive Mixing Probability Scheme in Mixed Gibbs Sampling MIMO Signal Detection

Abstract

This paper proposes an adaptive mixing probability scheme for mixed Gibbs sampling (MGS) or MGS with maximum ratio combining (MRC) in multiple-input multiple-output (MIMO) demodulation. In the conventional MGS algorithm, the mixing probability is fixed. Thus, if a search point is captured by a local minimum, it takes a larger number of samples to escape. In the proposed scheme, the mixing probability is increased when a candidate transmit symbol vector is captured by a local minimum. Using the adaptive mixing probability, the numbers of candidate transmit symbol vectors searched by demodulation algorithms increase. The proposed scheme in MGS as well as MGS with MRC reduces an error floor level as compared with the conventional scheme. Numerical results obtained through computer simulation show that the bit error rates of the MGS as well as the MGS with MRC reduces by about 1/100 when the number of iterations is 100 in a 64×64 MIMO system.