Waveform design is a critical technology for orthogonal time-frequency space (OTFS) integrated sens-ing and communication (ISAC) systems. Existing research mainly focuses on the design of multiple-input multiple-output (MIMO)-OTFS communication waveforms or the design of dual-functional OTFS waveforms for single-input single-output (SISO) systems, which results in degraded per-formance in dynamic, multi-user ISAC scenarios. To address these limitations, the paper mainly investigates waveform op-timization for MIMO-OTFS ISAC systems, which formulates the problem as minimizing the weighted integrated sidelobe level (WISL) under peak-to-average power ratio (PAPR) and multi-user interference (MUI) energy constraints. Due to its non-convex nature with multiple constraints, the problem is challenging to solve. To address the complicated optimization problem, an adaptive penalty analytic subproblem decompo-sition (APASD) method is proposed. First, auxiliary variables are introduced to decompose the original problem into several subproblems with analytic solutions. Then, leveraging the structure of the subproblems, we derive the corresponding analytic solutions. Finally, the penalty parameters are adap-tively updated based on the residuals, and the overall problem is iteratively refined until convergence. Simulation results demonstrate that the proposed method can achieve a lower sidelobe level while ensuring the achievable sum-rate, and shows better performance than existing methods.
Feng et al. (Sun,) studied this question.