Abstract:

As a simplified version of Spatial Modulation （SM）， Generalized Space Shift Keying （GSSK） has been widely used in massive Multiple-Input Multiple-Output （MIMO） systems. It can better solve the problems such as Inter-Channel Interference （ICI）， Inter-Antenna Synchronization （IAS）， and multiple Radio Frequency （RF） links in traditional MIMO technology. To solve the problem of high computational complexity of the Maximum Likelihood （ML） detection algorithm for GSSK systems， a low-complexity GSSK signal detection algorithm based on Compressed Sensing （CS） theory was proposed by combining Subspace Tracking （SP） and ML detection algorithms in CS， and presetting the threshold. First， the improved SP algorithm was used to obtain partial Transmit Antenna Combinations （TACs）. Secondly， the set of search antennas was shrunk by deleting partial antenna combinations. Finally， the ML algorithm and the preset threshold were used to estimate the TACs. The results of simulation experiments show that the computational complexity of the proposed algorithm is significantly lower than that of ML detection algorithm， and the Bit Error Rate （BER） performance is almost the same as that of ML detection algorithm， which verify the effectiveness of the proposed algorithm.

Key words: Generalized Space Shift Keying (GSSK), Multiple-Input Multiple-Output (MIMO), Compressed Sensing (CS), Subspace Pursuit (SP), Maximum Likelihood (ML) detection

摘要：

广义空移键控（GSSK）作为空间调制（SM）的一种简化形式，被广泛应用于大规模多输入多输出（MIMO）系统，以更好地解决传统MIMO技术中的信道间干扰（ICI）、天线间同步（IAS）和多射频（RF）链路等问题。针对GSSK系统最大似然（ML）检测算法计算复杂度高的问题，结合压缩感知（CS）中的子空间追踪（SP）算法和ML检测算法，并结合阈值的设置，提出一种基于CS理论的低复杂度GSSK信号检测算法。首先，用改进的SP算法获得部分发送天线组合（TAC）；其次，删除部分天线组合，缩小搜索天线组合的集合；最后，利用ML算法和预设的门限估计发送天线组合。仿真实验结果表明，所提算法的计算复杂度明显低于ML检测算法，同时误比特率（BER）性能逼近ML检测算法，验证了所提算法的有效性。

关键词: 广义空移键控, 多输入多输出, 压缩感知, 子空间追踪, 最大似然检测