Waveform Design for Integrated Sensing and Communications With PAPR Constraint

Abstract

This letter investigates the peak-to-average-power ratio (PAPR)-controllable waveform design problem in an integrated sensing and communication (ISAC) system, aiming to minimize downlink multi-user interference energy and maximize the detection probability of multiple-input multiple-output (MIMO) radar. The waveform design is formulated as a weighted optimization problem based on signal similarity to achieve a flexible trade-off between sensing and communication performance. The problem is non-convex, and we thus propose an iterative waveform design algorithm. We validate the effectiveness of our proposed scheme by comparing it with benchmark strategies for communication and sensing performance, demonstrating that our approach provides significant advantages in both communication and radar performance, as well as a flexible trade-off between the two functions.