广义空间调制系统的正则化OMP检测算法

在广义空间调制（GSM）系统中，最大似然（ML）检测可以取得最优的检测性能，然而其计算复杂度随激活天线数的增加急剧增长。针对这一问题，提出了一种基于稀疏重构理论的低复杂度检测算法——正则化正交匹配追踪（ROMP）算法。该算法首先根据信道矩阵和当前残差的内积选取多个候选激活天线索引，接着对候选天线索引按正则化标准进行可靠性验证，剔除错误索引，缩小信号的搜索空间，最后通过求解最小二乘问题估计信号。仿真结果表明，与经典的正交匹配追踪（OMP）算法相比，所提算法以少许复杂度的增加为代价极大提升了检测性能，能够在检测性能与复杂度之间取得更好的折中。

A regularized OMP detection algorithm for generalized spatial modulation systems

The optimal detection of generalized spatial modulation(GSM) system is the Maximum Likelihood(ML) algorithm. However,the computational complexity of ML detection increases significantly with the increase of the number of active antennas. To solve this problem,a low-complexity detection algorithm based on sparse reconstruction,termed as Regularized Orthogonal Matching Pursuit(ROMP) algorithm,is proposed. The algorithm starts by producing an estimate of the plausible active antennas indices according to correlation between the MIMO channels and the residual,then removes wrong indexes based on the regularization criteria and hence the search space is shrunk. Finally,it estimates GSM signal by involving the LS problem. Simulation results show that the proposed algorithm can improve the detection performance at the cost of slightly increased complexity compared with the conventional orthogonal matching pursuit(OMP) detector,and a better tradeoff between the performance and complexity is achieved.