{"title":"Low-Complexity Centralized Multi-Cell Radio Resource Allocation for 5G URLLC","authors":"A. Karimi, K. Pedersen, P. Mogensen","doi":"10.1109/WCNC45663.2020.9120469","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of down-link centralized multi-cell scheduling for ultra-reliable lowlatency communications in a fifth generation New Radio (5G NR) system. We propose a low-complexity centralized packet scheduling algorithm to support quality of service requirements of URLLC services. Results from advanced 5G NR system-level simulations are presented to assess the performance of the proposed solution. It is shown that the centralized architecture significantly improves the URLLC latency. The proposed algorithm achieves gains of 99% and 90% URLLC latency reduction in comparison to distributed scheduling and spectral efficient dynamic point selection.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC45663.2020.9120469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper addresses the problem of down-link centralized multi-cell scheduling for ultra-reliable lowlatency communications in a fifth generation New Radio (5G NR) system. We propose a low-complexity centralized packet scheduling algorithm to support quality of service requirements of URLLC services. Results from advanced 5G NR system-level simulations are presented to assess the performance of the proposed solution. It is shown that the centralized architecture significantly improves the URLLC latency. The proposed algorithm achieves gains of 99% and 90% URLLC latency reduction in comparison to distributed scheduling and spectral efficient dynamic point selection.
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