Abstract:
Partial transfer sequence (PTS) is an effective method for filter bank multicarrier (FBMC) to reduce peak-to-average power ratio (PAPR). However, PTS method selects the optimal phase factor via exhaustive search, which inevitable results in high computational complexity. In order to overcome this shortcoming, this paper presents a new PTS-based method. Firstly, based on the traditional PTS segmentation method, this paper introduces an odd-partial transfer sequence(OPTS) segmentation method, which uses staggered segmentation for odd subblocks and random segmentation for even subblocks. By combining the advantages of staggered segmentation and random segmentation, this proposed method can effectively improve the PAPR performance of the system, meanwhile, reduce the computational complexity. Secondly, this paper proposes a scaled particle swarm optimization (SPSO) algorithm by incorporating the scaling factor into the traditional PSO algorithm. It is known that the conventional particle swarm optimization (PSO) algorithm has a slow convergence rate in the iteration process and is prone to fall into local optimal in high-dimensional space. Aiming at the above shortcoming, this paper proposes an improved PSO algorithm, SPSO algorithm, whose main idea is to use the scaling factor to control the particle speed, and obtain better PAPR performance with lower computational complexity and faster convergence speed. It will slightly increase PAPR value via integrating SPSO algorithm into OPTS and can attain better performance in terms of complexity, and significantly improve the spectrum utilization. Finally, simulation results verify the effectiveness of the new method.