AI 中文总结
研究基于透射式可重构智能表面（TRIS）收发器的信息感知与通信一体化（ISAC）系统，在完美和不完美信道状态信息下，通过分数规划、主元最小化等方法设计发射波束成形，最大化系统能量效率，数值结果验证算法有效性及系统增益。
AI 中文摘要
本文采用一种新型透射式可重构智能表面（TRIS）收发器来实现支持通信和感知的一体化传感与通信（ISAC）系统。在完美和不完美信道状态信息（CSI）下，研究了TRIS收发器的发射波束成形设计，以在满足用户最小速率保证、对传感目标的最小波束方向图增益和每个天线功率约束的条件下最大化系统能量效率（EE）。由于分数目标和非凸约束，相应的EE最大化问题求解具有挑战性。特别是在不完美CSI下，产生的半无限约束使问题更加复杂。对于完美CSI情况，首先应用分数规划（FP）方法获得更易处理的速率函数重新表述，然后基于主元最小化（MM）框架提出迭代算法。对于不完美CSI情况，利用S - 过程将半无限不等式约束转换为线性矩阵不等式（LMI），并借助松弛变量进一步开发高效的基于MM的算法。数值结果证明了所提算法的收敛性和有效性，并验证了基于TRIS收发器的ISAC系统的EE增益。
英文摘要
In this paper, a novel transmissive reconfigurable intelligent surface (TRIS) transceiver is employed to enable an integrated sensing and communication (ISAC) system supporting both communication and sensing. Under both perfect and imperfect channel state information (CSI), we study the transmit beamforming design for the TRIS transceiver to maximize the system energy efficiency (EE), subject to per-user minimum-rate guarantees, a minimum beampattern gain toward the sensing target, and per-antenna power constraints. The corresponding EE maximization problems are challenging to solve due to the fractional objective and non-convex constraints. In particular, under imperfect CSI, the resulting semi-infinite constraints further complicate the problem. For the perfect CSI case, we first apply the fractional programming (FP) methodology to obtain more tractable reformulations of the rate functions, and then propose an iterative algorithm based on the majorization-minimization (MM) framework. For the imperfect CSI case, we utilize the S-Procedure to transform the semi-infinite inequality constraints into linear matrix inequalities (LMIs), and further develop an efficient MM-based algorithm with the aid of slack variables. Numerical results demonstrate the convergence and effectiveness of the proposed algorithms and validate the EE gains of the TRIS transceiver-enabled ISAC system.
