5G Centralized Multi-Cell Scheduling for URLLC: Algorithms and System-Level Performance

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)
96 Downloads (Pure)

Abstract

We study centralized radio access network (C-RAN) with multi-cell scheduling algorithms to overcome the challenges for supporting ultra-reliable low-latency communications (URLLC) in the fifth-generation new radio (5G NR) networks. Low-complexity multi-cell scheduling algorithms are proposed for enhancing the URLLC performance. In comparison with the conventional distributed scheduling, we show that the C-RAN architecture can significantly reduce undesirable queuing delay of URLLC traffic. The gain of user scheduling with different metrics and the benefit of packet segmentation are analyzed. The performance of the proposed solutions is evaluated with an advanced 5G NR compliant system-level simulator with high degree of realism. The results show that the centralized multi-cell scheduling achieves up to 60% latency improvement over the traditional distributed scheduling while fulfilling the challenging reliability of URLLC. It is shown that segmentation brings additional performance gain for both centralized and distributed scheduling. The results also highlight the significant impact of channel- and delay-aware scheduling of URLLC payloads.

Original languageEnglish
Article number8529183
JournalIEEE Access
Volume6
Pages (from-to)72253 - 72262
Number of pages10
ISSN2169-3536
DOIs
Publication statusPublished - 2018

Fingerprint

Scheduling
Communication
Scheduling algorithms
Network architecture
Telecommunication traffic
Simulators

Keywords

  • 5G
  • URLLC
  • packet scheduling
  • scheduling metric
  • segmentation

Cite this

@article{cdf22c7307d946c3b4e8d3469866c1fd,
title = "5G Centralized Multi-Cell Scheduling for URLLC: Algorithms and System-Level Performance",
abstract = "We study centralized radio access network (C-RAN) with multi-cell scheduling algorithms to overcome the challenges for supporting ultra-reliable low-latency communications (URLLC) in the fifth-generation new radio (5G NR) networks. Low-complexity multi-cell scheduling algorithms are proposed for enhancing the URLLC performance. In comparison with the conventional distributed scheduling, we show that the C-RAN architecture can significantly reduce undesirable queuing delay of URLLC traffic. The gain of user scheduling with different metrics and the benefit of packet segmentation are analyzed. The performance of the proposed solutions is evaluated with an advanced 5G NR compliant system-level simulator with high degree of realism. The results show that the centralized multi-cell scheduling achieves up to 60{\%} latency improvement over the traditional distributed scheduling while fulfilling the challenging reliability of URLLC. It is shown that segmentation brings additional performance gain for both centralized and distributed scheduling. The results also highlight the significant impact of channel- and delay-aware scheduling of URLLC payloads.",
keywords = "5G, URLLC, packet scheduling, scheduling metric, segmentation",
author = "Ali Karimidehkordi and Pedersen, {Klaus I.} and Mahmood, {Nurul Huda} and Jens Steiner and Mogensen, {Preben Elgaard}",
year = "2018",
doi = "10.1109/ACCESS.2018.2880289",
language = "English",
volume = "6",
pages = "72253 -- 72262",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "IEEE",

}

5G Centralized Multi-Cell Scheduling for URLLC : Algorithms and System-Level Performance. / Karimidehkordi, Ali; Pedersen, Klaus I.; Mahmood, Nurul Huda; Steiner, Jens; Mogensen, Preben Elgaard.

In: IEEE Access, Vol. 6, 8529183, 2018, p. 72253 - 72262.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - 5G Centralized Multi-Cell Scheduling for URLLC

T2 - Algorithms and System-Level Performance

AU - Karimidehkordi, Ali

AU - Pedersen, Klaus I.

AU - Mahmood, Nurul Huda

AU - Steiner, Jens

AU - Mogensen, Preben Elgaard

PY - 2018

Y1 - 2018

N2 - We study centralized radio access network (C-RAN) with multi-cell scheduling algorithms to overcome the challenges for supporting ultra-reliable low-latency communications (URLLC) in the fifth-generation new radio (5G NR) networks. Low-complexity multi-cell scheduling algorithms are proposed for enhancing the URLLC performance. In comparison with the conventional distributed scheduling, we show that the C-RAN architecture can significantly reduce undesirable queuing delay of URLLC traffic. The gain of user scheduling with different metrics and the benefit of packet segmentation are analyzed. The performance of the proposed solutions is evaluated with an advanced 5G NR compliant system-level simulator with high degree of realism. The results show that the centralized multi-cell scheduling achieves up to 60% latency improvement over the traditional distributed scheduling while fulfilling the challenging reliability of URLLC. It is shown that segmentation brings additional performance gain for both centralized and distributed scheduling. The results also highlight the significant impact of channel- and delay-aware scheduling of URLLC payloads.

AB - We study centralized radio access network (C-RAN) with multi-cell scheduling algorithms to overcome the challenges for supporting ultra-reliable low-latency communications (URLLC) in the fifth-generation new radio (5G NR) networks. Low-complexity multi-cell scheduling algorithms are proposed for enhancing the URLLC performance. In comparison with the conventional distributed scheduling, we show that the C-RAN architecture can significantly reduce undesirable queuing delay of URLLC traffic. The gain of user scheduling with different metrics and the benefit of packet segmentation are analyzed. The performance of the proposed solutions is evaluated with an advanced 5G NR compliant system-level simulator with high degree of realism. The results show that the centralized multi-cell scheduling achieves up to 60% latency improvement over the traditional distributed scheduling while fulfilling the challenging reliability of URLLC. It is shown that segmentation brings additional performance gain for both centralized and distributed scheduling. The results also highlight the significant impact of channel- and delay-aware scheduling of URLLC payloads.

KW - 5G

KW - URLLC

KW - packet scheduling

KW - scheduling metric

KW - segmentation

UR - http://www.scopus.com/inward/record.url?scp=85056543507&partnerID=8YFLogxK

U2 - 10.1109/ACCESS.2018.2880289

DO - 10.1109/ACCESS.2018.2880289

M3 - Journal article

VL - 6

SP - 72253

EP - 72262

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

M1 - 8529183

ER -