Cubic metric (CM) is a more precise measure to compute the large envelope fluctuations of orthogonal frequency division multiplexing signals. In this study, we use the partial transmit sequence method to reduce the high CM of signals. Despite the dramatic CM reduction ability of the partial transmit sequence method, its computational complexity is very high because of an exhaustive search over all possible combinations of phase factors. In order to overcome the search complexity of the partial transmit sequence method, we introduce an effective and fast convergence optimizer called a chaotic differential search algorithm (CDSA). The CDSA is a population based optimization method to solve the complex, large-scale and non-linear problems. Simulation results show the superiority of the proposed CDSA compared with several counterpart algorithms in terms of search complexity and CM mitigation performance.
