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

Yizhou Jiang, Xiujun Zhang, Xiaofeng Zhong, Shidong Zhou

TL;DR

This work tackles coexisting eMBB and random-arrival URLLC under a hybrid-TTI system by introducing a dual-scheduler framework: an eMBB scheduler at the start of each eMBB TTI selects coding redundancy, while a URLLC scheduler at each mini-slot preempts RBs to accommodate URLLC traffic with guaranteed latency. The method relies on URLLC arrival statistics rather than exact future knowledge, predicts preemption patterns, and uses a sigmoid BLER model to adapt eMBB coding. Key contributions include a deterministic greedy URLLC scheduler with proportional fairness, a queuing-theory-based analysis of preemption patterns, and a BLER-prediction mechanism to balance throughput and reliability under random URLLC arrivals. Simulations show near-optimal performance, achieving roughly 98% of the upper-bound throughput and improved one-shot BLER compared with baselines, demonstrating practical impact for dynamic resource scheduling in 5G/6G-like networks.

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.

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

TL;DR

This work tackles coexisting eMBB and random-arrival URLLC under a hybrid-TTI system by introducing a dual-scheduler framework: an eMBB scheduler at the start of each eMBB TTI selects coding redundancy, while a URLLC scheduler at each mini-slot preempts RBs to accommodate URLLC traffic with guaranteed latency. The method relies on URLLC arrival statistics rather than exact future knowledge, predicts preemption patterns, and uses a sigmoid BLER model to adapt eMBB coding. Key contributions include a deterministic greedy URLLC scheduler with proportional fairness, a queuing-theory-based analysis of preemption patterns, and a BLER-prediction mechanism to balance throughput and reliability under random URLLC arrivals. Simulations show near-optimal performance, achieving roughly 98% of the upper-bound throughput and improved one-shot BLER compared with baselines, demonstrating practical impact for dynamic resource scheduling in 5G/6G-like networks.

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.
Paper Structure (24 sections, 13 equations, 4 figures)

This paper contains 24 sections, 13 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Time-Frequency Resource Granularity
  4. Channel Model and CSI Knowledge
  5. Traffic Model
  6. Criteria for Evaluating the Performance
  7. Schedule Rule
  8. Joint Coding
  9. Receiver
  10. Scheduler Design
  11. URLLC Scheduler
  12. Scheduler Framework
  13. Deterministic Greedy URLLC Scheduler
  14. eMBB Scheduler and MCS Configuration
  15. The Distribution of $N_p(\tau)$
  16. ...and 9 more sections

Figures (4)

  • Figure 1: Time-Frequency Resource Granularity
  • Figure 2: Schedulers in two timescales.
  • Figure 3: Throughput vs URLLC arrival rate for three methods
  • Figure 4: BLER vs URLLC arrival rate for three methods