Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems

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Description/Abstract

Abstract—Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative two-level optimisation loop. An efficient global optimisation search algorithm called the repeated weighted boosting search is employed at the upper level to identify the unknown MIMO channel model while an enhanced ML sphere detector called the optimised hierarchy reduced search algorithm aided ML detector is used at the lower level to perform the ML detection of the transmitted data. A simulation example is included to demonstrate the effectiveness of these two schemes.