AI 中文总结
本文提出联合通信与控制框架，推导相关LQG代价并设计波束成形方法，所提方法性能优于迫零基准，可平衡通信与控制干扰。
AI 中文摘要
本文提出了一种联合通信与控制（JCC）框架，其中基站（BS）同时为多个通信用户（CU）提供服务，并以闭环方式控制物理装置。在下行链路中，基站生成的控制输入被传输至装置并在装置处恢复，无线致动失真被纳入装置状态演化过程；在上行链路中，装置状态被上报至基站，并通过卡尔曼滤波器（KF）进行跟踪，以用于后续控制输入的生成。为刻画通信-控制干扰下的长期控制性能，本文推导了有限和无限时域线性二次高斯（LQG）代价，直接将波束成形设计与装置状态演化关联起来。随后，针对向量值和标量值控制输入，本文构建了JCC波束成形问题，以在满足每个用户通信信干噪比（SINR）要求的前提下最小化无限时域LQG代价。对于向量情况，本文针对所得非凸问题开发了一种基于二阶锥规划（SOCP）的连续凸逼近方法；对于标量情况，本文推导了闭式无限时域LQG代价，并通过基于SOCP的二分法最优刻画了通信-控制帕累托边界，其最优性源于标量控制代价相对于控制SINR的严格单调性。数值结果表明，推导的代价与蒙特卡洛模拟结果高度吻合，KF可准确跟踪真实装置状态轨迹，且所提方法始终优于迫零基准，这证实了平衡通信-控制干扰的益处，尤其是在空间自由度（DoF）有限的场景下。
英文摘要
A joint communication and control (JCC) framework is proposed, where a base station (BS) simultaneously serves multiple communication users (CUs) and controls a physical plant in a closed loop. In the downlink, BS-generated control inputs are transmitted to and recovered at the plant, with wireless actuation distortion incorporated into the plant-state evolution. In the uplink, the plant state is reported to the BS and tracked by a Kalman filter (KF) for subsequent control-input generation. To characterize long-term control performance under communication-control interference, finite- and infinite-horizon linear quadratic Gaussian (LQG) costs are derived, directly linking beamforming design to plant-state evolution. JCC beamforming problems are then formulated for vector- and scalar-valued control inputs to minimize the infinite-horizon LQG cost subject to per-user communication signal-to-interference-plus-noise ratio (SINR) requirements. For the vector case, a second-order cone programming (SOCP)-based successive convex approximation method is developed for the resulting nonconvex problem. For the scalar case, a closed-form infinite-horizon LQG cost is derived, and the communication-control Pareto boundary is optimally characterized by an SOCP-based bisection method. Its optimality follows from the strict monotonicity of the scalar control cost with respect to the control SINR. Numerical results show that the derived costs closely match Monte Carlo simulations, the KF accurately tracks the ground-truth plant-state trajectory, and the proposed methods consistently outperform the zero-forcing benchmark. This confirms the benefit of balancing communication-control interference, especially with limited spatial degrees of freedom (DoFs).
CommentsThis work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. The abstract has been slightly edited to satisfy the arXiv character limit
