Integrated sensing and communication (ISAC) opens up new service possibilities for sixth-generation (6G) systems, where both communication and sensing (C&S) functionalities co-exist by sharing the same hardware platform and radio resource. In this paper, we investigate the waveform design problem in a downlink multi-user and multi-target ISAC system under different C&S performance preferences. The multi-user interference (MUI) may critically degrade the communication performance. To eliminate the MUI, we employ the constructive interference mechanism into the ISAC system, which saves the power budget for communication. However, due to the conflict between C&S metrics, it is intractable for the ISAC system to achieve the optimal performance of C&S objective simultaneously. Therefore, it is important to strike a trade-off between C&S objectives. By virtue of the multi-objective optimization theory, we propose a weighted Tchebycheff-based transformation method to re-frame the C&S trade-off problem as a Pareto-optimal problem, thus effectively tackling the constraints in ISAC systems. Finally, simulation results reveal the trade-off relation between C&S performances, which provides insights for the flexible waveform design under different C&S performance preferences in MIMO-ISAC systems.

翻译：集成感知与通信（ISAC）为第六代（6G）系统开辟了新的服务可能性，其中通信与感知（C&S）功能通过共享相同的硬件平台和无线电资源而共存。本文研究了在不同C&S性能偏好下的下行多用户多目标ISAC系统中的波形设计问题。多用户干扰（MUI）可能严重降低通信性能。为消除MUI，我们将建设性干扰机制引入ISAC系统，从而节省了用于通信的功率预算。然而，由于C&S指标之间存在冲突，ISAC系统难以同时实现C&S目标的最优性能。因此，在C&S目标之间取得权衡至关重要。借助多目标优化理论，我们提出了一种基于加权切比雪夫的转换方法，将C&S权衡问题重新构建为一个帕累托最优问题，从而有效处理ISAC系统中的约束。最后，仿真结果揭示了C&S性能之间的权衡关系，这为MIMO-ISAC系统中根据不同C&S性能偏好进行灵活波形设计提供了见解。