An agent based particle swarm optimization for PAPR reduction of OFDM systems

Orthogonal frequency division multiplexing (OFDM) is usually regarded as a spectral efficient multicarrier modulation technique, yet it suffers from a high peak to average power ratio (PAPR) problem. Partial transmit sequences (PTS) is one of the most well-known schemes to reduce the PAPR in OFDM systems. However, the conventional PTS scheme requires an exhaustive searching over all combinations of allowed phase factors. Consequently, the computational complexity increases exponentially with the number of the sub-blocks. Particle swarm optimization (PSO) algorithm is a recently proposed approach to solve the optimization problem of finding the phase factors of the PTS. In this paper, we propose an agent based particle swarm optimization for reducing computational complexity of the original PSO (OPSO) technique. Simulation results show that the agent based PSO (APSO) compare to the original PSO can effectively reduce the computational complexity of finding phase factors of the PTS.