Genetic Algorithm in Resource Allocation of RAN Slicing with QoS Isolation and Fairness

Xu Yang, Yapeng Wang, Ieok Cheng Wong, Yue Liu, Laurie Cuthbert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Radio access network (RAN) slicing is a challenging task, as different levels of isolation and fairness requirements need to be considered. In the context of resource allocation for RAN slicing, this paper addresses three major issues including maximizing the number of qualified users who are assigned the required bitrates, reducing the inter-slice QoS isolation between neighbouring cells caused by inter-cell interference and maximizing the fairness among all the slices. The proposed real number encoded Genetic Algorithm requires no prior knowledge about the network traffic models, provides high flexibility of slicing scheme, converges very quickly to evolve optimal/suboptimal solutions, and the dynamic weights of different objectives can adapt to the changes of users' scenarios.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE Latin-American Conference on Communications, LATINCOM 2020
EditorsRamiro Velazquez
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728189031
DOIs
Publication statusPublished - 18 Nov 2020
Event2020 IEEE Latin-American Conference on Communications, LATINCOM 2020 - Virtual, Santo Domingo, Dominican Republic
Duration: 18 Nov 202020 Nov 2020

Publication series

NameProceedings - 2020 IEEE Latin-American Conference on Communications, LATINCOM 2020

Conference

Conference2020 IEEE Latin-American Conference on Communications, LATINCOM 2020
Country/TerritoryDominican Republic
CityVirtual, Santo Domingo
Period18/11/2020/11/20

Keywords

  • Fairness
  • Genetic Algorithm
  • QoS isolation
  • network slicing
  • resource allocation

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