Wireless Control over Edge Networks: Joint User Association and Communication-Computation Co-Design
Zhilin Liu, Yiyang Li, Huijun Xing, Ye Zhang, Jie Xu, Shuguang Cui
TL;DR
The paper addresses end-to-end latency minimization in a multi-BS wireless networked control system with MEC under HRLLC constraints. It introduces a TDMA-based cascaded communication/computation protocol and leverages massive MIMO to serve multiple sensors/actuators, formulating a non-convex optimization problem to jointly optimize BS-sensor/actuator association, uplink/downlink power, and time allocation. An alternating optimization algorithm with successive convex approximation and problem relaxations solves the non-convex program, ensuring convergence. Numerical results show the proposed joint design substantially reduces the closed-loop latency and improves stability compared with benchmarks, with TDMA outperforming FDMA especially when computation resources are constrained.
Abstract
This paper studies a wireless networked control system with multiple base stations (BSs) cooperatively coordinating the wireless control of a number of subsystems each consisting of a plant, a sensor, and an actuator. In this system, each sensor first offloads the sensing data to its associated BS, which then employs mobile edge computing (MEC) to process the data and sends the command signals back to the actuator for remote control. We consider the time-division-multiple-access (TDMA) service protocol among different BSs to facilitate the cascaded communication and computation process, in which different BSs implement the uplink data collection and downlink command broadcasting over orthogonal time slots. We also employ the massive multiple-input multiple-output (MIMO) at BSs, based on which each BS serves its associated sensors or actuators over the same time-frequency resources via spatial multiplexing. Under this setup, we jointly design the association between BSs and sensors/actuators as well as the joint communication and computation resource allocation, with the objective of minimizing the closed-loop control latency of the multiple subsystems while ensuring their control stability. The optimization takes into account the transmission uncertainty caused by both the hyper reliable and low-latency communications (HRLLC) and the inter-user interference , as well as the communication and computation resource constraints at distributed nodes. To solve the challenging non-convex joint optimization problem, we develop an efficient algorithm by employing the techniques of alternating optimization and successive convex approximation (SCA). Numerical results show that the proposed joint BS-sensor/actuator association and resource allocation design significantly outperforms other heuristic schemes and frequency-division-multiple-access (FDMA) counterpart.