Implementation of Particle Swarm Optimization and Genetic Algorithms to Tackle the PAPR Problem of OFDM System

Abstract

A multi-carrier modulation technique, which represented in this paper as orthogonal-frequency-division-multiplexing (OFDM), ensured wireless high-speed data transmission. The transmission of modulated symbols uses a large number of subcarriers in the OFDM system. Consequently, the OFDM signals have an extended dynamic range, or a high output power peak envelope fluctuation or high PAPR. To mitigate the PAPR, in this paper, we implement two algorithms to reduce the output power envelope fluctuation of the OFDM system, namely PSO and GA. Also, the PTS method and PAPR in OFDM systems difficulty described briefly. We present an OFDM system through the use of conventional PTS based on PSO and GA. The simulation result shows that both evolutionary approaches outperform the conventional PTS OFDM in-terms of reducing the Peak-to-Average-Power-Ratio (PAPR). Furthermore, the performance of the PSO algorithm is found to be better than GA in-terms of its simplicity and the time execution. On the other hand, the GA algorithm outperforms the PSO and the conventional OFDM, in terms of the PAPR reduction.