MIMO系统中一种改进的盲MMSE空时多用户检测算法  

An improved blind MMSE space-time multiuser detection algorithm for MIMO system

作　　者：于文君[1] 何培宇[1] 黄如浩[1] 

机构地区：[1]四川大学电子信息学院,成都610065

出　　处：《信号处理》2010年第8期1275-1280,共6页Journal of Signal Processing

基　　金：通信抗干扰技术国家重点实验室资助项目(项目资助号:JG2007055)

摘　　要：针对MIMO系统,提出了一种改进的基于子空间的盲MMSE空时多用户检测算法。该算法结合MIMO系统的空间分集技术与Alamouti空时分组码方案,预估计MIMO信道信息并对信号子空间进行预处理,使用正交性能和稳态性能较好的NOOja算法跟踪信号子空间,在自适应过程中对特征值矩阵进行优化,去除迭代带来的噪声,解决了跟踪过程中信号特征值矩阵的近似估计会带来检测器性能恶化的问题。仿真结果表明这种算法,能有效地抑制多址干扰,抗远近效应能力强,尤其在低信噪比、远近效应明显的恶劣环境下,有稳定良好的性能表现。An improved linear minimum mean square error（MMSE） blind space-time multiuser detection （MUD） algorithm and its adaptive implementation based on subspace tracking is presented for the multiple-input muhiple-output Direct-Sequence Code-Divi- sion Multiple Access （ MIMO DS-CDMA） communication system. The proposed detection algorithm can be implemented by three steps for improvement. Firstly, the signal subspace can be pretreated by modifying a rough estimated signal subspace with MIMO wireless channels which gained by making full use of the available information of spatial diversity technique and space-time block coding （ ST- BC） scheme of MIMO system. Then the normalized orthogonal Oja （NOOja） algorithm with better orthogonality and stability than other algorithms is used to track the signal subspace. Aimed at the problem of detecting performance degradation on traditional algorithm caused by eigenvalue matrix approximate evaluation in every, iteration, eigenvalue matrix is optimized to remove noise in the adaptive process. Simulation results demonstrate that this algorithm is efficient to suppress multi-access interference （MAI） and combat the near- far resistant. In particular, it has good tracking ability and steady-state performance in the low SNR and distinct near-far resistant envi- ronment.

关 键 词：多输人多输出 空时分组码 盲多用户检测 修正信号子空间 Nooja 

分 类 号：TN914.5[电子电信—通信与信息系统]