Utility-Based Dynamic Resource Allocation in IEEE 802.11ax Networks: A Genetic Algorithm Approach

Taewon Song, Taeyoon Kim, Sangheon Pack

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    Orthogonal frequency division multiple access (OFDMA) is one of the critical features adopted in IEEE 802.11ax, where multiple stations can simultaneously access the wireless channel. Although appropriate sub-channel allocation is crucial to improving channel efficiency, the allocation method is vendor specific, since there is no central controller in the Wi-Fi network. In this chapter, we propose a utility-based dynamic resource allocation (UDRA) scheme for orthogonal frequency division multiple access resource management in IEEE 802.11ax WLANs. In UDRA, each access point (AP) obtains neighbor information using a newly proposed modified clear-to-send (M-CTS) frame by overhearing stations in an area overlapping with the other APs’ signal area. After that, we formulate the network-wise utility maximization problem, which considers both throughput and fairness, to determine which sub-channels should be allocated to which stations. Furthermore, we adopt a genetic algorithm to solve the derived optimization problem since the problem is known to be NP-hard. We map the proposed scheme, UDRA, onto a terminology of genetic algorithm. Extensive simulation results demonstrate that UDRA can guarantee comparable throughput to exhaustive search while preserving improved fairness with significantly reduced computing time.

    Original languageEnglish
    Title of host publicationWireless Networks (United Kingdom)
    PublisherSpringer Nature
    Pages65-80
    Number of pages16
    DOIs
    Publication statusPublished - 2022

    Publication series

    NameWireless Networks (United Kingdom)
    ISSN (Print)2366-1186
    ISSN (Electronic)2366-1445

    Bibliographical note

    Publisher Copyright:
    © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

    ASJC Scopus subject areas

    • Signal Processing
    • Information Systems
    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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