A Dynamic Resource Scheduling Algorithm Based on Traffic Prediction for Coexistence of eMBB and Random Arrival URLLC

TL;DR

This paper introduces a joint scheduling framework for eMBB and URLLC in 5G networks, utilizing traffic prediction to dynamically allocate resources and improve throughput without compromising reliability.

Contribution

It proposes a novel hybrid-TTI scheduling algorithm that predicts URLLC traffic to optimize eMBB coding redundancy and resource preemption.

Findings

Enhanced eMBB throughput with maintained reliability

Effective URLLC traffic support through immediate preemption

Traffic prediction improves resource allocation efficiency

Abstract

In this paper, we propose a joint design for the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and random low-latency communication (URLLC) with different transmission time intervals (TTI): an eMBB scheduler operating at the beginning of each eMBB TTI to decide the coding redundancy of eMBB code blocks, and a URLLC scheduler at the beginning of each mini-slot to perform immediate preemption to ensure that the randomly arriving URLLC traffic is allocated with enough radio resource and the eMBB traffic keeps acceptable one-shot transmission successful probability and throughput. The framework for schedulers under hybrid-TTI is developed and a method to configure eMBB code block based on URLLC traffic arrival prediction is implemented. Simulations show that our work improves the throughput of eMBB traffic without sacrificing the reliablity while supporting randomly arriving URLLC traffic.