Joint Scheduling of URLLC and eMBB Traffic in 5G Wireless Networks

• Published in: IEEE/ACM transactions on networking Vol. 28; no. 2; pp. 477 - 490
• Main Authors: Anand, Arjun, de Veciana, Gustavo, Shakkottai, Sanjay
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; 5G systems; Bandwidth; Broadband; Broadband communication; Communications traffic; Computer simulation; Decisions; Iterative methods; Mobile computing; Network latency; Optimal scheduling; Optimization; Piercing; Reliability; Resource allocation; Resource management; Resource scheduling; URLLC traffic; Wireless communication; Wireless networks; Wireless scheduling
• DOI: 10.1109/TNET.2020.2968373
• ISSN: 1063-6692

Emerging 5G systems will need to efficiently support both enhanced mobile broadband traffic (eMBB) and ultra-low-latency communications (URLLC) traffic. In these systems, time is divided into slots which are further sub-divided into minislots. From a scheduling perspective, eMBB resource allocations occur at slot boundaries, whereas to reduce latency URLLC traffic is pre-emptively overlapped at the minislot timescale, resulting in selective superposition/puncturing of eMBB allocations. This approach enables minimal URLLC latency at a potential rate loss to eMBB traffic.We study joint eMBB and URLLC schedulers for such systems, with the dual objectives of maximizing utility for eMBB traffic while immediately satisfying URLLC demands. For a linear rate loss model (loss to eMBB is linear in the amount of URLLC superposition/puncturing), we derive an optimal joint scheduler. Somewhat counter-intuitively, our results show that our dual objectives can be met by an iterative gradient scheduler for eMBB traffic that anticipates the expected loss from URLLC traffic, along with an URLLC demand scheduler that is oblivious to eMBB channel states, utility functions and allocation decisions of the eMBB scheduler. Next we consider a more general class of (convex/threshold) loss models and study optimal online joint eMBB/URLLC schedulers within the broad class of channel state dependent but minislot-homogeneous policies. A key observation is that unlike the linear rate loss model, for the convex and threshold rate loss models, optimal eMBB and URLLC scheduling decisions do not de-couple and joint optimization is necessary to satisfy the dual objectives. We validate the characteristics and benefits of our schedulers via simulation.