A Low Complex Modified Grey Wolf Optimization Model for OFDM Peak Power Reduction

摘要

Orthogonal frequency division multiplexing (OFDM) or multicarrier modulation is an essential signal processing technique in new generation wireless gadgets owing to its potential to support fast and spectrally efficient transmission. One of the major limitations of OFDM systems is the peak-to-average power ratio (PAPR) of transmit data. In this article, a novel meta heuristic algorithm called modified grey wolf optimizer is used to boost the computing performance of subcarrier phase factor search in the undisputed partial transmit sequence method. The proposed modified grey wolf optimizer (mGWO) has a balancing between exploration and exploitation phases while searching for peak power carriers and brings out a nearly optimal performance but with less number of iterations. The objective is to propose low complex computing algorithm without compromising the output quality. The simulation results of proposed mGWO-PTS model assure improvements around 20 to 25 percent from that of the comparative counterparts such as GWO-PTS, PSO-PTS, and etc.