中文摘要：

针对衰落信道中酉空时调制的识别问题,提出两种酉空时信号与传统空时码的识别方案。最大似然识别法利用信道转移概率密度构造平均似然比和广义似然比分类函数,依据不同码字似然比的差异完成分类,在对数域处理从而降低计算复杂度。最大似然识别法可在无信道状态信息的条件下完成识别,当已知信道状态信息时识别性能可大幅提高。高阶统计特性识别法利用随机矩阵的矩生成函数产生高阶联合矩和高阶联合累积量,依据酉空时信号特殊的高阶统计特性实现识别。高阶统计特性识别法需要信道状态信息,且其准确性会受信道估计的影响,但实现简单;通过增加接收天线数量在各种方案中均可改善识别性能,4根接收天线相对2根接收天线的增益,无CSI的最大似然法为7-10d B,有CSI的高阶统计特性法可达45d B。仿真结果验证了所提方案的有效性。

英文摘要：

For the purpose of recognizing unitary space-time modulation （USTM）signals in fading channels,we propose two identification schemes by making full use of USTM signal features.One is maximum likelihood recognition scheme which employs channel transfer probability density function （PDF）to construct average likelihood ratio and generalized likelihood ratio classification functions.This scheme accomplishes classification with the difference of the likelihood ratios of different space-time signals,and its calculation complexity can be decreased by processing in log domaln.The scheme based on maximum likelihood rule can realize identification without channel state information （CSI）and can give a better performance on a large scale when CSI is avallable.Another is high order statistics recognition scheme which uses moment generating function to generate high order joint moment and high order joint cumulant.This scheme realizes recognition by the special high order statistics of unitary space-time signals.The proposed schemes can identify unitary space-time signal from conventional space-time codes.High order statistics scheme needs CSI and its performance is affected by the accuracy of channel estimation,but its calculation complexity is low.In both schemes,the recognition performance can be improved by increasing the number of receive antennas.Compared with 2 receive antennas,the galn for 4 receive antennas is 7-10dB for maximum likelihood method without CSI and is about 45dB for high order statistics method with CSI.Simulation shows the effectiveness of the proposed schemes.