LL-PGS: A Lightweight and Low-Latency Proactive Grant Scheduling Algorithm for Industrial IoT

To efficiently realize the low-latency scheduling of ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) services in Industrial Internet of Things (IIoT), we propose a lightweight and, low-latency proactive grant scheduling (LL-PGS) algorithm. In the proposed LL-PGS, a lightweight channel-queue prediction algorithm, and an adaptive two-tier scheduling priority adjustment module are organically integrated. Through the cooperation between above modules, the proposed LL-PGS facilitates the low-latency and on-demand physical resource blocks (PRBs) scheduling without extra state report and grant feedback. Extensive simulation results demonstrate that the proposed LL-PGS can significantly reduce the signaling overhead and uplink latency without sacrificing throughput. Compared with conventional scheduling algorithms including round robin (RR), proportional fair (PF), exponential proportional fair (EXP/PF), and modification of largest weighted delay first (M-LWDF), the proposed LL-PGS can increase the average uplink throughput for eMBB services by 12.42%, and reduce latency for URLLC services to 1ms.

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Publication Details

Journal
IEEE Wireless Communications Letters
Published
2024-11-13
DOI
https://doi.org/10.1109/lwc.2024.3497324
Citations
3
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
0.63

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article

LL-PGS: A Lightweight and Low-Latency Proactive Grant Scheduling Algorithm for Industrial IoT

Jin Li, Shouhua Lai, Dongxu Zhang
3 citations
IEEE Wireless Communications Letters
Advanced Wireless Network Optimization
0.63
article

LL-PGS: A Lightweight and Low-Latency Proactive Grant Scheduling Algorithm for Industrial IoT

Jin Li, Shouhua Lai, Dongxu Zhang
article en
3 citations

Abstract

To efficiently realize the low-latency scheduling of ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) services in Industrial Internet of Things (IIoT), we propose a lightweight and, low-latency proactive grant scheduling (LL-PGS) algorithm. In the proposed LL-PGS, a lightweight channel-queue prediction algorithm, and an adaptive two-tier scheduling priority adjustment module are organically integrated. Through the cooperation between above modules, the proposed LL-PGS facilitates the low-latency and on-demand physical resource blocks (PRBs) scheduling without extra state report and grant feedback. Extensive simulation results demonstrate that the proposed LL-PGS can significantly reduce the signaling overhead and uplink latency without sacrificing throughput. Compared with conventional scheduling algorithms including round robin (RR), proportional fair (PF), exponential proportional fair (EXP/PF), and modification of largest weighted delay first (M-LWDF), the proposed LL-PGS can increase the average uplink throughput for eMBB services by 12.42%, and reduce latency for URLLC services to 1ms.

IEEE Wireless Communications LettersVol. 14(2)
Beijing University of Posts and Telecommunications (CN)
National Key Research and Development Program of China
Industry, innovation and infrastructure
Openalex Percentile: Top 31%
Advanced Wireless Network Optimization
0.63
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