Ofdm Papr Reduction by ANN-Aided Tone Reservation via PSO

Orthogonal frequency division multiplexing (OFDM) is a well-known modulation technique in wireless communications, due to its spectral efficiency and robustness against frequency-selective fading. Nevertheless, OFDM signals confront a significant challenge in the form of a high peak-to-average power ratio (PAPR), leading to distortion when transmitted through power amplifiers (PAs). This research introduces an artificial neural network-aided tone reservation with particle swarm optimization (ANN-TR-PSO) PAPR reduction technique to address this issue. The proposed method not only attains superior PAPR reduction gains but also reduces transmission computational complexity while maintaining bit error rate (BER) integrity. The outcome of this technique will enable efficient and reliable deployment for real-time applications in 5 G and beyond communications.