Secure and Efficient PAPR Reduction in OFDM Using PTS Based Nonlinear Variation Convergence Factor with Spotted Hyena Optimization

The Orthogonal Frequency Division Multiplexing (OFDM) is a widely used transmission technique that allows feasible modulation and demodulation in wireless communication.In the OFDM system, the high Peak-to-Average Power Ratio (PAPR) is a complex task when finding the optimum phase factor.Therefore, this research proposed a Partial Transmit Sequence-Nonlinear variation convergence factor with Spotted Hyena Optimization (PTS-NSHO) for reducing PAPR in OFDM.The PTS-NSHO finds the optimum phase factor by recognizing other possible local areas in global space through precise and quick convergence.For signal encoding and decoding in OFDM, the Low-Density Parity-Check (LDPC) and Space Time Block Code (STBC) are applied.The Quadrate Amplitude Modulation (QAM-16) is used for signal modulation and demodulation.The PTS is used for PAPR reduction in which the phase factor is optimized through the proposed PTS-NSHO algorithm.The Additive White Gaussian Noise (AWGN) channel is used to transmit signals from transmitter to receiver.The Symbol Error Rate (SER), Bit Error Rate (BER) and Complementary Cumulative Distribution Function (CCDF) are used to estimate the PTS-NSHO performance.The PTS-NSHO achieved less PAPR of 3.8dB for CCDF=10-3 which is better than existing optimization such as Partial Transmit Sequence-Chaotic Sand Cat Swarm Optimization (PTS-CSCSO).