降低OFDM系统复杂度的改进SLM算法

摘要 为了降低正交频分复用(OFDM)系统中传统选择性映射(SLM)算法的计算复杂度，提高系统的频谱利用效率，提出了基于转换向量(conversion vectors)与随机筛选序列(random selection sequences)相结合的选择性映射(CR-SLM)算法.CR-SLM算法是将原始信号序列等分，然后对于数据序列的前半部分与转换向量相乘进行循环卷积，对于数据序列后半部分进行随机序列筛选，筛选出最优序列.最后将两部分输出序列合并生成候选序列，筛选出最优序列进行传输.仿真结果表明:CR-SLM算法在保持与传统SLM 算法PAPR性能相近的情况下，较大幅度降低了计算复杂度.
Abstract：In order to reduce the computational complexity of the traditional selective mapping(SLM)algorithm in OFDM(orthogonal frequency division multiplexing) systems， and improve the spectral efficiency of the system， a CR-SLM algorithm based on the combination of conversion vectors and random selection sequences was proposed. In this algorithm， the data sequence is equally divided into two parts. For the first half of the data sequence IFFT(inverse fast Fourier transform) is taken， and then circular convolution is performed. Random sequence screening is applied for the second half section to reduce the complexity. Finally， the two output sequences are grouped together to generate candidate sequences， and the optimal sequence is selected for transmission. The simulation results show that the CR-SLM algorithm greatly reduces the computational complexity while maintaining the PAPR(peak to average power ration) close to that of the conventional SLM algorithm.