一种重叠Alamouti码的最大似然检测优化算法

An Improved Algorithm of Maximum Likelihood Receiver for Overlapped Alamouti Codes

针对准正交重叠Alamouti码(Overlapped Alamouti Code,OAC)采用最大似然(maximum likelihood,ML)接收机检测时译码复杂度高的缺点,提出了一种ML译码优化算法。利用等价信道矩阵具有部分正交性的特点,将等价信道矩阵拆分成2个相互正交的子等价信道矩阵,使得在检测每个符号分组时可分别检测2个较短分组,从而降低了ML接收机的译码复杂度。改进算法保持了与ML译码相近的误码率性能,而运算量大幅度降低,从而克服了ML译码复杂度高的缺点。

An improved ML detection algorithm is proposed to overcome the disadvantage of OAC that decoding complexity is too high. The characteristics that the equivalent channel matrix has part of orthogonality are used to split the equivalent channel matrix into two mutually orthogonal sub-equivalent channel matrices. It makes the decoding of each symbol group may respectively decode two short packets, which reduces the complexity of ML decoding receiver. The proposed algorithm can greatly reduce the computational complexity, and has the same performance as the ML detection.So it can overcome the defect of ML receiver.