The advancement of wireless communication systems toward 5G and beyond is spurred by the demand for high data rates, exceedingly dependable low-latency communication, and extensive connectivity that aligns with sensing requisites such as advanced high-resolution sensing and target detection. Consequently, embedding sensing into communication has gained considerable attention. In this work, we propose an alternative approach for optimizing integrated sensing and communication (ISAC) waveform for target detection by concurrently maximizing the power of the communication signal at an intended user and minimizing the multi-user and sensing interference. We formulate the problem as a non-disciplined convex programming (NDCP) optimization and we use a distribution-based approach for interference cancellation. Precisely, we establish the distribution of the communication signal and the multi-user communication interference received by the intended user, and thereafter, we establish that the sensing interference can be distributed as a centralized Chi-squared if the sensing covariance matrix is idempotent. We design such a matrix based on the symmetrical idempotent property. Additionally, we propose a disciplined convex programming (DCP) form of the problem, and using successive convex approximation (SCA), we show that the solutions can reach a stable waveform for efficient target detection. Furthermore, we compare the proposed waveform with state of the art radar-communication waveform designs and demonstrate its superior performance by computer simulations.

翻译：无线通信系统向5G及未来演进的发展，是由对高数据速率、极高可靠低延迟通信以及大规模连接的需求所推动的，这些需求与高分辨率感知和目标检测等感知要求相契合。因此，将感知功能嵌入通信系统已引起广泛关注。本文提出一种集成感知与通信（ISAC）波形优化的替代方法，通过同时最大化目标用户的通信信号功率并最小化多用户干扰与感知干扰，以提升目标检测性能。我们将该问题建模为非规范凸规划（NDCP）优化问题，并采用基于分布的干扰消除方法。具体而言，我们建立了目标用户接收到的通信信号与多用户通信干扰的分布模型，并进一步证明：若感知协方差矩阵为幂等矩阵，则感知干扰可服从中心化卡方分布。我们基于对称幂等性设计了该矩阵。此外，我们提出了该问题的规范凸规划（DCP）形式，并利用逐次凸逼近（SCA）方法，证明解能够收敛到适用于高效目标检测的稳定波形。最后，我们将所提波形与现有先进的雷达通信波形设计进行对比，并通过计算机仿真验证其优越性能。