English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Emerging 5G systems will need to efficiently support both enhanced mobilebroadband traffic (eMBB) and ultra-low-latency communications (URLLC) traffic.In these systems, time is divided into slots which are further sub-divided intominislots. From a scheduling perspective, eMBB resource allocations occur atslot boundaries, whereas to reduce latency URLLC traffic is pre-emptivelyoverlapped at the minislot timescale, resulting in selectivesuperposition/puncturing of eMBB allocations. This approach enables minimalURLLC latency at a potential rate loss to eMBB traffic.  We study joint eMBB and URLLC schedulers for such systems, with the dualobjectives of maximizing utility for eMBB traffic while immediately satisfyingURLLC demands. For a linear rate loss model (loss to eMBB is linear in theamount of URLLC superposition/puncturing), we derive an optimal jointscheduler. Somewhat counter-intuitively, our results show that our dualobjectives can be met by an iterative gradient scheduler for eMBB traffic thatanticipates the expected loss from URLLC traffic, along with an URLLC demandscheduler that is oblivious to eMBB channel states, utility functions andallocation decisions of the eMBB scheduler. Next we consider a more generalclass of (convex/threshold) loss models and study optimal online jointeMBB/URLLC schedulers within the broad class of channel state dependent butminislot-homogeneous policies. A key observation is that unlike the linear rateloss model, for the convex and threshold rate loss models, optimal eMBB andURLLC scheduling decisions do not de-couple and joint optimization is necessaryto satisfy the dual objectives. We validate the characteristics and benefits ofour schedulers via simulation.

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