An exhaustive entropy based SLM method for PAPR reduction of OFDM systems

Abstract

Orthogonal frequency division multiplexing (OFDM) is an attractive technology to provide immense improvements in wireless transmission capacity but high peak-to-average power ratio (PAPR) is a major drawback of OFDM system. Selected mapping (SLM) scheme has good performance for PAPR reduction. It requires the transmitting data to be multiplied by random phase sequences. However, the sequences are pseudo-random which will decrease the method effectiveness. Exhaustive entropy is introduced in this paper which can identify the strength of random phase sequences property. Then an exhaustive entropy based SLM method is proposed. The scheme improves the effectiveness of random phase sequences by selecting the larger exhaustive entropy of them. Simulation results show that the PAPR reduction performance is better than that of conventional SLM through this method.