Resource Allocation and User Pairing for Rate Splitting Multiple Access Based Wireless Networked Control Systems

Wireless networked control systems (WNCSs) have emerged as a new paradigm in industrial Internet of Things (IIoT), where base station (BS) transmits control commands generated by the remote controller to actuators of multiple control subsystems through shared wireless channels. This paper investigates a novel rate splitting multiple access (RSMA) enabled ultra-reliable and low-latency (URLLC) transmission design for industrial control applications in WNCSs, where control commands are splitted and transmitted with finite blocklength regime. This design aims to maximize the system sum rate (SR) by optimizing beamforming at BS, rate control for each control subsystem, and user pairing between control subsystems and subcarriers, while ensuring the control stability requirements for all control subsystems. We first derive the control convergence constraint into a communication reliability constraint expressed in terms of outage probability. Then we propose a nested iterative algorithm adopting alternating optimization (AO). During the inner iteration, we propose a resource allocation method leveraging successive convex approximation (SCA) to jointly optimize beamforming and rate control, while during the outer iteration, a hypergraph game-theoretic based matching method is provided to obtain the optimal pairing result between control subsystems and subcarriers. Simulation results demonstrate that the proposed transmission design outperforms existing schemes in terms of communication rate and control cost.

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Publication Details

Journal
IEEE Transactions on Communications
Published
2024-12-24
DOI
https://doi.org/10.1109/tcomm.2024.3522044
Citations
13
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
2.71
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article

Resource Allocation and User Pairing for Rate Splitting Multiple Access Based Wireless Networked Control Systems

Fanqin Zhou, Xudong Wang, Lei Feng, Zhixiang Yang et al.
13 citations
IEEE Transactions on Communications
Advanced Wireless Network Optimization
2.71
article

Resource Allocation and User Pairing for Rate Splitting Multiple Access Based Wireless Networked Control Systems

Fanqin Zhou, Xudong Wang, Lei Feng, Zhixiang Yang, Hongyang Du, Dusit Niyato, Wenjing Li
article en
13 citations

Abstract

Wireless networked control systems (WNCSs) have emerged as a new paradigm in industrial Internet of Things (IIoT), where base station (BS) transmits control commands generated by the remote controller to actuators of multiple control subsystems through shared wireless channels. This paper investigates a novel rate splitting multiple access (RSMA) enabled ultra-reliable and low-latency (URLLC) transmission design for industrial control applications in WNCSs, where control commands are splitted and transmitted with finite blocklength regime. This design aims to maximize the system sum rate (SR) by optimizing beamforming at BS, rate control for each control subsystem, and user pairing between control subsystems and subcarriers, while ensuring the control stability requirements for all control subsystems. We first derive the control convergence constraint into a communication reliability constraint expressed in terms of outage probability. Then we propose a nested iterative algorithm adopting alternating optimization (AO). During the inner iteration, we propose a resource allocation method leveraging successive convex approximation (SCA) to jointly optimize beamforming and rate control, while during the outer iteration, a hypergraph game-theoretic based matching method is provided to obtain the optimal pairing result between control subsystems and subcarriers. Simulation results demonstrate that the proposed transmission design outperforms existing schemes in terms of communication rate and control cost.

IEEE Transactions on CommunicationsVol. 73(7)
Beijing University of Posts and Telecommunications (CN), Nanyang Technological University (SG), University of Hong Kong (HK)
Openalex Percentile: Top 9%
Advanced Wireless Network Optimization
2.71
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