论文部分内容阅读
提出了一种基于选择性映射(SLM)降低OFDM系统峰均功率比(PAPR)的自适应多级SLM(AMSLM)方法。该方法通过逐级实施选择性映射,各级采用不同的相位加权因子集合,使得级间候选向量之间的相关性降低,从而使PAPR性能获得了更大地改善;同时设定适当的门限值,若当前级所获得的PAPR最低值大于该门限值,则自动进入下一级优化过程,否则终止整个优化过程。仿真结果表明,与SLM方法相比,AMSLM方法可以获得几乎相同或者更好的PAPR性能,同时,计算复杂度明显降低,如当总级数为4时,AMSLM方法的计算复杂度较SLM降低了47.81%。
An adaptive multi-level SLM (AMSLM) method is proposed based on selective mapping (SLM) to reduce the peak-to-average power ratio (PAPR) of OFDM systems. By implementing selective mapping step by step and using different sets of phase weighting factors at all levels, the method reduces the correlation between candidate vectors of the levels, so that PAPR performance can be greatly improved. At the same time, an appropriate threshold value If the lowest PAPR value obtained by the current level is greater than the threshold, the next level optimization process is automatically performed, otherwise, the entire optimization process is terminated. Simulation results show that compared with SLM, AMSLM can achieve almost the same or better PAPR performance and reduce computational complexity significantly. For example, when the total number of ranks is 4, the computational complexity of AMSLM is lower than that of SLM 47.81%.