Hojjat Emami - Department of Computer Engineering, University of Bonab, Bonab, Iran

This paper presents a new nature-inspired optimization algorithm for the cubic metric (CM) reduction problem, namely enhanced sunflower optimization (ESFO) algorithm. The incentive mechanism of ESFO is enhancing the optimization ability of the sunflower optimization (SFO) algorithm by introducing a powerful pollination strategy. The ESFO is used to overcome the computational complexity of the PTS scheme in solving CM reduction.The objective of ESFO-PTS is to find out a near-optimal permutation of phase factors that minimizes the high CM of OFDM signals. With a test on several CM reduction scenarios, the ESFO-PTS algorithm achieved better results than its counterparts

Swarm intelligence algorithm, ESFO algorithm, PTS, Cubic metric reduction