空间调制系统下改进的QRD-M检测算法

空间调制（SM）系统中性能最优的最大似然（ML）检测算法复杂度很高，用基于信道矩阵QR分解的M算法（QRD-M）可以降低复杂度，但传统QRD-M算法检测时，每层都保留固定的M个节点，仍会造成额外的计算量。针对传统QRD-M算法中存在的问题，提出一种低复杂度的动态M值QRD-M检测算法——LC-QRD-dM。LC-QRD-dM算法利用设计的阈值与累积分支度量值进行比较，每层自适应地选择不超过M的保留节点数，相对于传统QRD-M算法以牺牲少量性能为代价大大降低了复杂度。接着又针对该改进算法在信道衰落较深时会产生较大误码率的问题，进一步提出一种基于信道状态的动态M值QRD-M检测算法——CS-QRD-dM。CS-QRD-dM利用LC-QRD-dM的原理，在低信噪比（SNR）时，每层根据阈值选择不小于M的保留节点数；在高信噪比时，每层则选择不超过M的保留节点数。理论分析和仿真结果表明：相比传统QRD-M，CS-QRD-dM在低信噪比时有约1.3 dB的信噪比增益（误码率为10^-2），以增加少量复杂度为代价，显著地改善了检测性能；在高信噪比时，其检测性能及复杂度与LC-QRD-dM相同。

Improved QRD-M detection algorithm for spatial modulation system

In Spatial Modulation (SM) system, the Maximum Likelihood (ML) detection algorithm with the best performance has high complexity, while the complexity can be reduced by M-algorithm based on QR decomposition (QRD-M) of channel matrix. However, when the traditional QRD-M algorithm is used, fixed M nodes were chosen at each layer, which leads to additional computation. Therefore, for the problem of the traditional QRD-M algorithm, a Low-Complexity QR-Decomposition M-algorithm with dynamic value of M (LC-QRD-dM) was proposed. In LC-QRD-dM, by comparing the designed threshold with the cumulative branch metrics, the number of reserved nodes that does not exceed M was adaptively selected at each layer, thus reducing the computational complexity with the cost of a small amount of performance. Then, concerning the high bit error rate of LC-QRD-dM with deep channel fading, QR-Decomposition M-algorithm with dynamic value of M based on Channel State (CS-QRD-dM) was further proposed. Based on the principle of LC-QRD-dM, the number of reserved nodes that do not less than M was selected by the threshold value at each layer when the Signal-to-Noise Ratio (SNR) is not high; and the number of reserved nodes that do not exceed M was selected by the threshold value at each layer when the SNR is high. Theoretic analysis and simulation results show that, compared with the traditional QRD-M algorithm, CS-QRD-dM achieves about 1.3 dB SNR advantage (when the bit error rate is 10^-2) at low SNR, which can significantly improve the detection performance at the cost of small complexity increase; and its detection performance and complexity are the same as LC-QRD-dM at high SNR.