Selective Mapping OFDM without Side Information Using a Low Complexity ML Decoder

Abstract

Selective mapping (SLM) has been proposed for peak to average power reduction (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. With SLM, multiple sequences are generated by multiplying independent phase se- quences with the original data and the sequence with the lowest PAPR is chosen for transmission. Hence, to determine the selected sequence at the receiver, side information must be sent along with the data. Previously, a maximum-likelihood (ML) decoder was proposed to eliminate this side information. However, this adds significant complexity to the receiver. In this paper, we first propose a partial SLM (P-SLM) technique using combinations of time-domain sequences. We then show that P-SLM can significantly reduce the ML decoder complexity. We examine the bit error rate (BER) performance of the simplified decoder over additive white Gaussian noise (AWGN) and fading channels. The results show that the proposed decoder has almost identical BER performance to that of the previous decoding algorithm while achieving very low computational complexity.