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

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.