Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Journal of University of Electronic Science and Technology of China》 2017-01
Add to Favorite Get Latest Update

An Enhanced MCMC Algorithm for MIMO Systems Based on Max-Log Updating

HU Jian-hao;ZHOU Jiang-yun;HE Shuai-ning;CHEN Jie-nan;National Key Lab of Science and Technology on Communications,University of Electronic Science and Technology of China;  
In this paper, an enhanced Markov chain Monte Carlo(MCMC) algorithm based on max-log updating is proposed for multiple input multiple output(MIMO) system. The max-log updating can generate the list vectors to simply the complexity of the calculation of the extrinsic log-likelihood ratios(LLRs) efficiently. Meanwhile, it avoids calculating probability distribution per bit in conventional MCMC. However, the proposed MCMC detection suffers from the so called "stalling" problem, where the Markov chain may be trapped into local optimal state. Thus, we also propose three enhancement technologies: 1) biased processing, i.e., updating randomly in a given biased interval; 2) reinitialized processing, i.e., reinitialize the Markov chain under the sub-optimal states; 3) clipped processing, i.e., reprocessing the LLR with clipping. Simulation results show that the proposed algorithm can remedy the "stalling" problem efficiently with reduced complexity, and can achieve 2 d B performance gains with 10% less complexity than MMSE-PIC.
【Fund】: 国家自然科学基金(6150010678 61371104)
【CateGory Index】: TN919.3
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved