Optimal phase searching of PTS using modified genetic algorithm for PAPR reduction in OFDM systems

In this paper, a novel genetic algorithm assisted partial transmit sequence (NGA-PTS) is proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM). However, the search complexity of the optimum PTS (OPTS) scheme is too large for the typical number of sub-blocks. Therefore, some artificial intelligence methods, such as genetic algorithm technique, and particle swarm optimization, are introduced to reduce the complexity. As traditional GA-PTS (TGA-PTS) technique risks finding a suboptimal solution, how to avoid this disadvantage of TGA-PTS is an interest topic. In order to obtain a better suboptimal solution, a phase factor optimal pair technique and an abandon/introduction new chromosome technique are proposed in GA here. Simulation results show that the proposed scheme achieves a significant improvement over the TGA-PTS scheme in PAPR. Furthermore, by use of the inherent diversity of constellation for each OFDM candidate, in the receiver part, the proposed scheme enables data recovery without any side information. Simulation results show the efficiency of the proposed scheme.