Preparing Wi-Fi 7 for Healthcare Internet-of-Things.

Area of Science:

• Wireless communication systems
• Internet of Things (IoT) in healthcare
• Network scheduling algorithms

Background:

• The Healthcare Internet of Things (H-IoT) enables continuous health monitoring for early disease detection and ambient assisted living (AAL).
• Uplink (UL) transmission delays in Wireless Local Area Networks (WLANs) using Orthogonal Frequency Division Multiple Access (OFDMA) can be unacceptable for delay-sensitive H-IoT applications due to their random traffic patterns.

Purpose of the Study:

• To propose a novel UL OFDMA scheduler for the upcoming IEEE 802.11be (Wi-Fi 7) standard.
• To ensure compliance with stringent latency requirements essential for H-IoT and AAL applications.
• To enhance overall system performance, including fairness and throughput, for H-IoT services.

Main Methods:

• Development of a UL OFDMA scheduler specifically designed for the IEEE 802.11be standard.
• The scheduler intelligently allocates channel resources based on traffic class or access category.
• Evaluation of the scheduler's performance against existing state-of-the-art solutions.

Main Results:

• The proposed scheduler successfully achieves the required low latency for H-IoT applications.
• Demonstrated superior performance in terms of both fairness and throughput compared to current schedulers.
• Validation of the scheduler's effectiveness for delay-sensitive healthcare data transmission.

Conclusions:

• The developed IEEE 802.11be UL OFDMA scheduler is a viable solution for latency-critical H-IoT applications.
• This advancement supports the reliable implementation of continuous health monitoring and AAL.
• The scheduler offers significant improvements in network efficiency and user experience for healthcare services.