The full-duplex (FD) technology has the potential to radically evolve wireless systems, facilitating the integration of both communications and radar functionalities into a single device, thus, enabling joint communication and sensing (JCAS). In this paper, we present a novel approach for JCAS that incorporates a reconfigurable intelligent surface (RIS) in the near-field of an FD multiple-input multiple-output (MIMO) node, which is jointly optimized with the digital beamformers to enable JSAC and efficiently handle self-interference (SI). We propose a novel problem formulation for FD MIMO JCAS systems to jointly minimize the total received power at the FD node's radar receiver while maximizing the sum rate of downlink communications subject to a Cram\'{e}r-Rao bound (CRB) constraint. In contrast to the typically used CRB in the relevant literature, we derive a novel, more accurate, target estimation bound that fully takes into account the RIS deployment. The considered problem is solved using alternating optimization, which is guaranteed to converge to a local optimum. The simulation results demonstrate that the proposed scheme achieves significant performance improvement both for communications and sensing. It is showcased that, jointly designing the FD MIMO beamformers and the RIS phase configuration to be SI aware can significantly loosen the requirement for additional SI cancellation.

翻译：全双工（FD）技术具有从根本上变革无线系统的潜力，可将通信与雷达功能集成至单一设备，从而赋能联合通信与感知（JCAS）。本文提出了一种新颖的JCAS方法，该方法将可重构智能表面（RIS）置于全双工多输入多输出（MIMO）节点的近场区域，并与数字波束成形器联合优化，以支持联合感知与通信并高效处理自干扰（SI）。我们为FD MIMO JCAS系统提出了一种新颖的问题建模方法，旨在联合最小化FD节点雷达接收机处的总接收功率，同时在下行通信和速率最大化中引入克拉美罗界（CRB）约束。与相关文献中常用的CRB不同，我们推导了一种全新的、更精确的目标估计界，该界充分考虑了RIS部署的影响。该问题通过交替优化求解，并保证收敛至局部最优解。仿真结果表明，所提方案在通信与感知性能上均实现了显著提升。研究表明，通过联合设计FD MIMO波束成形器与RIS相位配置使其具备自干扰感知能力，可大幅降低对额外自干扰消除的需求。