TY  - JOUR
T1  - A Configured-Grant Scheduling Method for Ensuring Data Freshness under 5G URLLC Scenarios
AU  - Kim, Ji-Su 
AU  - Kim, Beom-Su 
JO  - The Journal of Korean Institute of Communications and Information Sciences
PY  - 2025
DA  - 2025/1/1
DO  - 10.7840/kics.2025.50.7.1021
KW  - 5G. OFDM
KW  - URLLC
KW  - low latency
KW  - grant-free scheduling
KW  - weighted age of information
AB  - One of the key application scenarios of 5G, URLLC (Ultra-Reliable and Low-Latency Communications), requires user traffic to be processed within 1 ms. To meet this requirement, prior studies have employed Configured-Grant scheduling methods, which allocate uplink resources in advance for periodically generated URLLC traffic, enabling efficient provision of ultra-low-latency services. However, these conventional Configured-Grant scheduling approaches primarily optimize system performance based on traditional metrics such as throughput, delay, and fairness, making it challenging to guarantee the timeliness of urgent data. To address this limitation, this paper proposes a novel Configured-Grant scheduling algorithm that ensures the timeliness of a URLLC traffic by incorporating AoI (Age of Information), a metric representing data freshness, combined with packet priority into the W-AoI (Weighted-AoI) metric. The proposed scheduler is implemented by extending the 5G-Lena module of the NS-3 network simulator. Performance evaluations demonstrate that the proposed approach achieves up to a 16.4% reduction in the average system AoI at a 1 ms transmission period compared to conventional scheduling methods, effectively improving data timeliness.