AAF-MH协作方案下的PARAFAC盲信号检测方法  

A PARAFAC Blind Signal Detection Algorithm for AAF-MH Cooperative Scheme

作　　者：韩曦[1] 袁超伟[1] 胡紫巍[1] 

机构地区：[1]北京邮电大学信息与通信工程学院,北京100876

出　　处：《北京邮电大学学报》2013年第1期82-85,90,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：国家自然科学基金项目(60872149)

摘　　要：多跳Alamouti放大转发(AAF-MH)协作方案的译码通常需要获取信道状态信息(CSI),在实际系统中,CSI的获取比较困难.针对此问题,提出了一种基于平行因子(PARAFAC)的盲信号检测方法.该方法将接收信号构建为包含信道、信号信息的PARAFAC模型,并使用双线性最小二乘算法进行拟合,以保证结果的全局收敛性.与恒模方法相比,该方法的拟合结果具有稳定性,并能实现参数估计的唯一性,在检测性能方面更具优势.仿真结果验证了理论分析的正确性.The decoding of multi-hop Alamouti amplify and forward （AAF-MH） cooperation scheme usu- ally needs channel state information, which is difficult to acquire in practical systems. To solve this prob- lem, a parallel factor （PARAFAC）-based blind signal detection algorithm is proposed. This algorithm transforms received signals into a PARAFAC model which contains channel and signal information, and uses the bilinear alternating least square for the global convergence. Compared with constant modulus al- gorithm, the proposed algorithm is with better performance, such as more stable fitting results, and can realize uniqueness of parameter estimation. Simulation is given to support the analysis.

关 键 词：平行因子 盲检测 多跳Alamouti放大转发 唯一性 

分 类 号：TN929.53[电子电信—通信与信息系统]