A novel artificial intelligence based wireless local area network channel access control scheme for low latency e‐health applications

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.