Liu, Zixin, Lv, Yunxin, Bi, Meihua, Zhai, Yanrong (2023) A novel artificial intelligence based wireless local area network channel access control scheme for low latency e‐health applications. IET Communications, 17 (17). pp. 1974-1983. ISSN 1751-8636. (doi:10.1049/cmu2.12668) (KAR id:102554)
PDF
Publisher pdf
Language: English
This work is licensed under a Creative Commons Attribution 4.0 International License.
|
|
Download this file (PDF/2MB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1049/cmu2.12668 |
Abstract
To effectively support low‐latency e‐health applications, a novel artificial intelligence‐based wireless local area network (WLAN) channel access control scheme named intelligent hybrid channel access (IHCA) is proposed and studied. In the IHCA scheme, each beacon interval comprises multiple cycles, with each cycle containing a contention‐free period (CFP) and a contention period (CP). By adopting an artificial neural network (ANN) and utilizing its calculation outputs to (1) decide whether to poll a hub during the CFP and (2) determine the initial backoff count (IBC) of each hub, polling of empty hubs during CFP can be reduced, and collisions during CP can be relieved. The authors’ simulation results show that the IHCA scheme can effectively reduce latency compared to the Hybrid coordination function Controlled Channel Access (HCCA) and the Request based Polling Access (RPA) reference designs.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1049/cmu2.12668 |
Uncontrolled keywords: | Electrical and Electronic Engineering, Computer Science Applications |
Subjects: | T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Funders: | National Natural Science Foundation of China (https://ror.org/01h0zpd94) |
SWORD Depositor: | JISC Publications Router |
Depositing User: | JISC Publications Router |
Date Deposited: | 20 Oct 2023 14:31 UTC |
Last Modified: | 15 Apr 2024 13:22 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/102554 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):