Title :
MMSE soft-interference-cancellation aided MCMC detection for MIMO systems
Author :
Xiao, Ke ; Su, Mingchao ; Guo, Shujun
Author_Institution :
Coll. of Inf. Eng., North China Univ. of Technol., Beijing, China
Abstract :
A novel MCMC detection algorithm in MEMO systems is proposed. The Gibbs samples are initialized through a new way after integrating the Minimum Mean Square Error soft-interference-cancellation (SIC-MMSE) algorithm and the convergence of the Markov chain is accelerated. Comparison with the conventional MCMC algorithm shows the novel algorithm performs better with equal number of Gibbs samples, that is, equal complexity. It is proved that our proposed SIC-MMSE-aided MCMC algorithm has superior performance.
Keywords :
MIMO communication; Markov processes; Monte Carlo methods; least mean squares methods; Gibbs samples; MCMC detection; MIMO systems; MMSE soft-interference-cancellation; Markov chain; minimum mean square error; Constellation diagram; Decoding; Detection algorithms; Detectors; Forward error correction; MIMO; Monte Carlo methods; Receiving antennas; Signal generators; Transmitting antennas; Minimum Mean Square Error (MMSE); Monte Carlo Markov Chain (MCMC); multiple-input multiple-output (MIMO); soft-interference-cancellation (SIC);
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3671-2
Electronic_ISBN :
978-1-4244-3672-9
DOI :
10.1109/ICIEEM.2009.5344250
