Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio

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Abstract

Ultra-reliable and low-latency communication (URLLC) is envisioned as a primary service class of the fifth generation mobile networks. URLLC applications demand stringent radio latency requirements of 1 millisecond with 99.999\% confidence. Obviously, the coexistence of the URLLC services and enhanced mobile broadband (eMBB) applications on the same spectrum imposes a challenging scheduling problem. In this paper, we propose an enhanced spatial preemptive scheduling framework for URLLC-eMBB traffic coexistence. The proposed scheduler ensures an instant and interference-free signal subspace for critical URLLC transmissions, while achieving best-effort eMBB performance. Furthermore, the impacted eMBB capacity is then recovered by limited network-assisted signaling. The performance of the proposed scheduler is evaluateeed by highly detailed system level simulations of the major performance indicators. Compared to the state-of-the-art multi-traffic schedulers from industry and academia, the proposed scheduler meets the stringent URLLC latency requirements, while significantly improving the achievable ergodic capacity.
Original languageEnglish
Title of host publication2018 IEEE Globecom Workshops (GC Wkshps)
Number of pages6
PublisherIEEE
Publication date2019
ISBN (Print)978-1-5386-4921-3
ISBN (Electronic)978-1-5386-4920-6
DOIs
Publication statusPublished - 2019
Event2018 IEEE Globecom Workshops (GC Wkshps) - Abu Dhabi, United Arab Emirates
Duration: 9 Dec 201813 Dec 2018

Conference

Conference2018 IEEE Globecom Workshops (GC Wkshps)
CountryUnited Arab Emirates
CityAbu Dhabi
Period09/12/201813/12/2018
SeriesIEEE Global Communications Conference (GLOBECOM) 2018

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Telecommunication traffic
Scheduling
Communication
Wireless networks
Industry

Cite this

Abdul-Mawgood Ali Ali Esswie, Ali ; Pedersen, Klaus I. / Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio. 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2019. (IEEE Global Communications Conference (GLOBECOM) 2018).
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title = "Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio",
abstract = "Ultra-reliable and low-latency communication (URLLC) is envisioned as a primary service class of the fifth generation mobile networks. URLLC applications demand stringent radio latency requirements of 1 millisecond with 99.999\{\%} confidence. Obviously, the coexistence of the URLLC services and enhanced mobile broadband (eMBB) applications on the same spectrum imposes a challenging scheduling problem. In this paper, we propose an enhanced spatial preemptive scheduling framework for URLLC-eMBB traffic coexistence. The proposed scheduler ensures an instant and interference-free signal subspace for critical URLLC transmissions, while achieving best-effort eMBB performance. Furthermore, the impacted eMBB capacity is then recovered by limited network-assisted signaling. The performance of the proposed scheduler is evaluateeed by highly detailed system level simulations of the major performance indicators. Compared to the state-of-the-art multi-traffic schedulers from industry and academia, the proposed scheduler meets the stringent URLLC latency requirements, while significantly improving the achievable ergodic capacity.",
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Abdul-Mawgood Ali Ali Esswie, A & Pedersen, KI 2019, Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio. in 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, IEEE Global Communications Conference (GLOBECOM) 2018, 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates, 09/12/2018. https://doi.org/10.1109/GLOCOMW.2018.8644070

Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio. / Abdul-Mawgood Ali Ali Esswie, Ali; Pedersen, Klaus I.

2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2019.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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T1 - Capacity Optimization of Spatial Preemptive Scheduling for Joint URLLC-eMBB Traffic in 5G New Radio

AU - Abdul-Mawgood Ali Ali Esswie, Ali

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N2 - Ultra-reliable and low-latency communication (URLLC) is envisioned as a primary service class of the fifth generation mobile networks. URLLC applications demand stringent radio latency requirements of 1 millisecond with 99.999\% confidence. Obviously, the coexistence of the URLLC services and enhanced mobile broadband (eMBB) applications on the same spectrum imposes a challenging scheduling problem. In this paper, we propose an enhanced spatial preemptive scheduling framework for URLLC-eMBB traffic coexistence. The proposed scheduler ensures an instant and interference-free signal subspace for critical URLLC transmissions, while achieving best-effort eMBB performance. Furthermore, the impacted eMBB capacity is then recovered by limited network-assisted signaling. The performance of the proposed scheduler is evaluateeed by highly detailed system level simulations of the major performance indicators. Compared to the state-of-the-art multi-traffic schedulers from industry and academia, the proposed scheduler meets the stringent URLLC latency requirements, while significantly improving the achievable ergodic capacity.

AB - Ultra-reliable and low-latency communication (URLLC) is envisioned as a primary service class of the fifth generation mobile networks. URLLC applications demand stringent radio latency requirements of 1 millisecond with 99.999\% confidence. Obviously, the coexistence of the URLLC services and enhanced mobile broadband (eMBB) applications on the same spectrum imposes a challenging scheduling problem. In this paper, we propose an enhanced spatial preemptive scheduling framework for URLLC-eMBB traffic coexistence. The proposed scheduler ensures an instant and interference-free signal subspace for critical URLLC transmissions, while achieving best-effort eMBB performance. Furthermore, the impacted eMBB capacity is then recovered by limited network-assisted signaling. The performance of the proposed scheduler is evaluateeed by highly detailed system level simulations of the major performance indicators. Compared to the state-of-the-art multi-traffic schedulers from industry and academia, the proposed scheduler meets the stringent URLLC latency requirements, while significantly improving the achievable ergodic capacity.

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