ESTIMATION OF LOG-LIKELIHOOD USING CONSTRAINED MARKOV-CHAIN MONTE CARLO SIMULATION
摘要
Log likelihood ratios for data bits transmitted in a multi-dimensional signal are estimated using multiple Markov chain Monte Carlo simulations (MCMC). The MCMC simulations can include constraining symbols based on a most-likely symbol to improve the likelihood of finding distances for non-most-likely symbols. The log likelihood ratios can be calculated based on distances of the most-likely symbol and the non-most-likely symbols.
申请公布号
WO2010008949(A2)
申请公布日期
2010.01.21
申请号
WO2009US49600
申请日期
2009.07.02
申请人
UNIVERSITY OF UTAH RESEARCH FOUNDATION;FARHANG, BEHROUZ;AKOUM, SALAM