Enabling Grant-Free URLLC for AoI Minimization in RAN-Coordinated 5G Health Monitoring System

• Published in: IEEE internet of things journal Vol. 10; no. 19; p. 1
• Main Authors: Kim, Beom-Su, Lim, Byung Hyun, Suh, Beomkyu, Ha, Sangtae, He, Ting, Shah, Babar, Kim, Ki-Il
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Adaptive algorithms; age of information; grant-free URLLC; joint scheduling; low-power sensors; Monitoring; Monitoring systems; Network latency; Performance evaluation; Resource allocation; Resource management; Scheduling; Sensors; Telemedicine; Ultra reliable low latency communication; Uplink; Wireless communication
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2023.3273521

Age of information (AoI) is used to evaluate the performance of 5G health monitoring systems because stale data can be fatal for patients with serious illness. Recently, grant-free ultra-reliable and low latency communications (URLLC) have shown greater potential of minimizing AoI than conventional grant-based approaches; however, existing grant-free schedulers cannot provide guaranteed performance in 5G health monitoring systems because they involve two fundamental problems in time and frequency domains, namely the joint scheduling problem and physical resource block (PRB) allocation. In this study, we investigate two resource allocation problems for the first time, aiming to enable grant-free URLLC to minimize AoI in 5G health monitoring systems. Specifically, we propose two adaptive solutions based on an open radio access network-coordinated wireless system: 1) a joint scheduling algorithm and 2) an adaptive PRB allocation algorithm. To verify the effectiveness of the proposed solutions, we built a simulation environment similar to a real health monitoring system and captured the performance variations under realistic deployment scenarios.