A Practical PAPR Minimization Algorithm for OFDM-Based JRC Systems via Linear Programming

Orthogonal frequency-division multiplexing (OFDM)-based joint radar communication (JRC) systems have signal distortion when the transmit signal has a high peak-to-average power ratio (PAPR). This is due to the nonlinear nature of the power amplifier. The problem of PAPR minimization is well-studied in the literature. However, most of the algorithms have high computational costs, making them impractical for real-time applications. To that end, we address this problem by proposing a linear programming (LP)-based algorithm that iteratively decreases the PAPR. More precisely, we solve the nonconvex PAPR minimization problem by solving a sequence of LP problems. The proposed method significantly reduces the PAPR of the initialized waveform within a short execution time and outperforms the existing techniques in terms of both radar sensing and communication performance.