A Low-Complexity Scheme to Reduce the PAPR of an OFDM Signal Using Taguchi-Genetic Algorithms

In this paper, we proposed a weighting factor estimation method for peak-to-average power ratio (PAPR) based on Taguchi-genetic algorithm (TGA) in an orthogonal frequency division multiplexing (OFDM) systems. Partial transmit sequences (PTS) is one of the most attractive 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 subblocks. In this study, a new PTS technique that uses a novel numerical stochastic optimization algorithm inspired from natural genetics and natural selection, designated as hybrid Taguchi-genetic algorithm (HTGA), for PAPR reduction in the OFDM system is introduced. The simulation results show that compared with the various stochastic search techniques developed previously, the proposed TGA-based PTS obtains the excellent PAPR performance with a low computational complexity.