In this paper, we investigate a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system under typical block-fading channels. As a non-trivial extension to most existing works on ISAC, both the training and transmission signals sent by the ISAC transmitter are exploited for sensing. Specifically, we develop two training and transmission design schemes to minimize a weighted sum of the mean-squared errors (MSEs) of data transmission and radar target response matrix (TRM) estimation. For the former, we first optimize the training signal for simultaneous communication channel and radar TRM estimation. Then, based on the estimated instantaneous channel state information (CSI), we propose an efficient majorization-minimization (MM)-based robust ISAC transmission design, where a semi-closed form solution is obtained in each iteration. For the second scheme, the ISAC transmitter is assumed to have statistical CSI only for reducing the feedback overhead. With CSI statistics available, we integrate the training and transmission design into one single problem and propose an MM-based alternating algorithm to find a high-quality solution. In addition, we provide alternative structured and low-complexity solutions for both schemes under certain special cases. Finally, simulation results demonstrate that the radar performance is significantly improved compared to the existing scheme that integrates sensing into the transmission stage only. Moreover, it is verified that the investigated two schemes have advantages in terms of communication and sensing performances, respectively.

翻译：本文研究典型块衰落信道下的多输入多输出集成感知与通信系统。作为对现有ISAC研究的重要拓展，本文同时利用ISAC发射机发送的训练信号与传输信号进行感知。具体而言，我们提出两种训练与传输设计方案，以最小化数据传输与雷达目标响应矩阵估计的均方误差加权和。针对第一种方案，首先优化训练信号以实现通信信道与雷达TRM的联合估计；随后基于估计得到的瞬时信道状态信息，提出一种基于高效最大化-最小化算法的鲁棒ISAC传输设计方案，该方案在每次迭代中均可获得半闭式解。第二种方案为降低反馈开销，假设ISAC发射机仅掌握统计CSI。在已知CSI统计特性的条件下，我们将训练与传输设计整合为单一优化问题，并提出基于MM的交替迭代算法以获得高质量解。此外，针对特定特殊场景，我们为两种方案分别提供了可替代的结构化低复杂度解决方案。仿真结果表明：相较于仅将感知功能集成于传输阶段的现有方案，本文所提方案的雷达性能显著提升；同时验证了所研究的两种方案分别在通信与感知性能方面各具优势。