 control can be treated as a constraint on communication reli- ability, which allows us to convert the co-design problem into a regular communication optimization problem. We prove that the formulated optimization problem is concave based on the conversion. Subsequently, we develop an iteration method to find the optimal bandwidth and power allocation. The rest of this chapter is organized as follows. In Section 14.2, the system model is pre- sented. In Section 14.3, the communication-control co-design method is proposed, where the optimal resource allocation problem is formulated with control performance constraint. In Section 14.4, the relationship between the communication and control subsystems is first discussed, and then an iteration method is proposed to obtain the optimal resource alloca- tion in terms of maximizing the communication SE. In Section 14.5, simulation results are provided to show the performance. Finally, Section 14.6 concludes the chapter. 14.2 System Model with Latency and Reliability Constraints In this section, we propose the system model by taking communication latency and reliability into consideration. As shown in Figure 14.1, we consider a typical cen- tralized real-time wireless communication-control system, where there are M static 1 The main control variables are state sampling period and control input gain, which jointly affect control convergence rate. Then, control convergence rate further affects the control performance, e.g. control cost or control stability. By constraint on control convergence rate, the state sampling period and control input gain are constrained. Thus, control convergence rate is considered as the control design in this chapter. 14 Optimizing Resource Allocation in URLLC for Real-Time Wireless Control Systems Sensor 1 Sensor 2 Sensor M Uplink Transmit sampling signals of the plant state Remote controller Base station Downlink Transmit control command signals Plant 1 Plant 2 Plant M Figure 14.1 Real-time wireless control system model. sensors transmitting s