Phase Optimization for PAPR Reduction in OFDM-LFM-CPM Waveform for Integrated Sensing and Communication

This study addresses the high peak-to-average power ratio (PAPR) challenge in orthogonal frequency division multiplexing-linear frequency modulation-continuous phase modulation (OFDM-LFM-CPM) integrated sensing and communication (ISAC) waveforms. To address this issue, we develop a particle swarm optimization (PSO)-based algorithm for PAPR reduction, which involves using PSO to iteratively optimize phase factors applied to the waveform, significantly improving PAPR performance. Simulation results demonstrate that this PSO-based optimization effectively reduces PAPR without degrading radar detection accuracy or increasing communication bit error rate (BER). Compared to the traditional partial transmit sequence (PTS) algorithm, it shows more stable and effective performance, highlighting its potential to enhance the overall performance of ISAC systems.