摘要
This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search points in each transmit antenna signal constellation instead of all hy-perplane. Both of the selection and search complexity can be reduced significantly. The method per-forms the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.
This paper proposes an efficient approximate Maximum Likelihood （ML） detection method for Multiple-Input Multiple-Output （MIMO） systems, which searches local area instead of exhaustive search and Selects valid search points in each transmit antenna signal constellation instead of all hyperplane. Both of the selection and search complexity can be reduced significantly. The method performs the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.
关键词
MIMO系统
信号检测
最大似然法
线性检测
Signal detection
Maximum Likelihood （ML）
Multiple-Input Multiple-Output （MIMO） system
