Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning

S Szott, K Kosek-Szott, P Gawłowicz… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …

Wider-bandwidth operation of IEEE 802.11 for extremely high throughput: challenges and solutions for flexible puncturing

S Kim, JH Yun - IEEE Access, 2020 - ieeexplore.ieee.org
This paper aims to explain the wideband operation of IEEE 802.11, illustrate the challenges
for wider-bandwidth support, and propose solutions. First, we describe the wideband …

A three-tier deep learning-based channel access method for WiFi networks

Y Huang, KW Chin - IEEE Transactions on Machine Learning …, 2023 - ieeexplore.ieee.org
Future WiFi networks require a channel access method that provides users with high
capacity. Such a method must consider 1) channel bonding, which improves the …

An on-demand channel bonding algorithm based on outage probability for large-scale industrial Internet of Things

W Sun, G Zhang, K Meng, G Han… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
In Industrial Internet of Things (IIoT), a large number of wireless nodes communicate through
limited channel resources. Using IEEE802. 11ac/ah with multiple users multiple-input …

IBAC: An intelligent dynamic bandwidth channel access avoiding outside warning range problem

R Karmakar, G Kaddoum - IEEE Transactions on Mobile …, 2022 - ieeexplore.ieee.org
IEEE 802.11 ax uses the concept of primary and secondary channels, leading to the
Dynamic Bandwidth Channel Access (DBCA) mechanism. By applying DBCA, a wireless …

Improving performance of high throughput wireless access networks-an experience in learning

S Chattopadhyay - Proceedings of the 23rd International Conference on …, 2022 - dl.acm.org
IEEE 802.11 n, IEEE 802.11 ax etc. are known as High Throughput Wireless Local Area
Networks standards. These standards are extended versions of the popular IEEE 802.11 …

Reinforcement Learning Approaches to Improve Spatial Reuse in Wireless Local Area Networks

Y Huang - 2022 - ro.uow.edu.au
The ubiquitous deployment of IEEE 802.11 based Wireless Local Area Networks (WLANs)
or WiFi networks has resulted in dense deployments of Access Points (APs) in an effort to …

[PDF][PDF] Echoing the Future: On-Device Machine Learning in Next-Generation Networks-A Comprehensive Survey

HB Pasandi, FB Pasandi, F Parastar, A Moradbeikie… - researchgate.net
On-device Machine Learning (on-deviceML) is the concept of bringing Machine Learning
models to the constraint device itself and making it smarter. Tiny Machine Learning (TinyML) …

[PDF][PDF] On-device ML For the Current and the Emerging Networks: A Survey on Current Approaches and Challenges

F Parastar, M Sepahi, M Moudi - researchgate.net
According to predictions, the number of connected devices to a network has reached an all-
time high, resulting in higher traffic and network density. That is why we want smarter and …