Leveraging Linear Quadratic Regulator Cost and Energy Consumption for Ultra-Reliable and Low-Latency IoT Control Systems

Abstract: To efficiently support the real-time control applications, networked control systems operating with ultra-reliable and low-latency communications (URLLCs) become fundamental technology for future Internet of things (IoT). However, the design of control, sensing and communications is generally isolated at present. In this paper, we propose the joint optimization of control cost and energy consumption for a centralized wireless networked control system. Specifically, with the ``sensing-then-control'' protocol, we first develop an optimization framework which jointly takes control, sensing and communications into account. In this framework, we derive the spectral efficiency, linear quadratic regulator cost and energy consumption. Then, a novel performance metric called the \textit{energy-to-control efficiency} is proposed for the IoT control system. In addition, we optimize the energy-to-control efficiency while guaranteeing the requirements of URLLCs, thereupon a general and complex max-min joint optimization problem is formulated for the IoT control system. To optimally solve the formulated problem by reasonable complexity, we propose two radio resource allocation algorithms. Finally, simulation results show that our proposed algorithms can significantly improve the energy-to-control efficiency for the IoT control system with URLLCs.