Using evolutionary computation technique for trade-off between performance peak-to average power ration reduction and computational complexity in OFDM systems

摘要

A low-complexity partial transmit sequence (PTS) technique for reducing the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) system is presented. However, PTS technique requires an exhaustive search over all combinations of allowed phase weighting factors, and the search complexity increases exponentially with the number of sub-blocks in OFDM system. Hence, there has been a trade-off between performance PAPR reduction and computational complexity in PTS OFDM system. The proposed is a sub-optimum PTS for PAPR reduction of OFDM system. Simulation results demonstrate that the superiority of evolutionary computation technique-particle swarm optimization (PSO) based on PTS which can be utilized for finding the optimum phase weighting factors, and can achieve the lower PAPR and computational complexity of OFDM systems. In addition, our evolutionary computation technique can be used to reduce reduction PAPR with comparable performance to genetic algorithm-based PTS, with much less computation cost.