PAPR reduction of OFDM signals using autocorrelation based SLM without side information

Aperiodic autocorrelation and power variance are two parameters that play an important role in PAPR reduction in OFDM symbols. In this paper, we have tackled the aperiodic autocorrelation factor and based on it, two algorithms have been proposed. In the first algorithm, called selective autocorrelation (SA), the value of first aperiodic autocorrelation coefficient is minimized to 1 for reducing the PAPR. In the second algorithm, called selected sequences with variable autocorrelation SLM (SSVA), multiple sequences are generated by modifying a fixed number of complex numbers. The one giving minimum PAPR is transmitted. Simulation results show significant reduction in PAPR. Further a novel technique based on data insertion is used to handle the side information generated by the two algorithms without degrading the PAPR performance.