Low-Complexity Hybrid QRD-MCMC MIMO Detection

Ronghui Peng, Koon Hoo Teo, Jinyun Zhang, Rong-Rong Chen

Abstract: In this paper, we propose a novel hybrid QRD- MCMC MIMO detector that combines the features of a QRD-M detector and a Markov chain Monte Carlo (MCMC) detector. The QRD-M algorithm is applied first to obtain initial estimates of the transmitted signal vector. Subsequently, the QRD-M estimate is used to initialize one of the Gibbs samplers for MCMC detection. The MCMC detection reduces the M parameter required by the QRD-M detector, while the QRD-M initialization effectively alleviates the well-known high-SNR problem in existing MCMC detectors. Performance of the QRD-M/MCMC detector is examined under both an idealized MIMO channel with perfect channel side information (CSI) and a practical IEEE 802.16e MIMO- OFDMA system with imperfect CSI. Numerical results show that, compared to the stand-alone QRD-M or MCMC detectors, the QRD-MCMC detector achieves superior performance at a reduced complexity.