Learning Contention Window Selection in Age of Information-Oriented IEEE 802.11 Networks
J Li, F Jian - 2023 IEEE 11th International Conference on …, 2023 - ieeexplore.ieee.org
We study the problem of selecting the contention window (CW) for age of information (AoI)-
oriented IEEE 802.11 networks using deep reinforcement learning (DRL) techniques. AoI …
oriented IEEE 802.11 networks using deep reinforcement learning (DRL) techniques. AoI …
A deep learning assisted approach for minimizing the age of information in a WiFi network
Motivated by the demands of time-sensitive applications, our paper studies methods for the
age of information (AoI) minimization over a WiFi Network. Specifically, the AoI of a labeled …
age of information (AoI) minimization over a WiFi Network. Specifically, the AoI of a labeled …
Scheduling the data transmission interval in IEEE 802.11 ad: A reinforcement learning approach
The IEEE 802.11 ad Wi-Fi standard enables communications in the unlicensed mm-wave
band at 60 GHz. Propagation at such frequencies accounts for increased path loss and …
band at 60 GHz. Propagation at such frequencies accounts for increased path loss and …
LUPMAC: A cross-layer MAC technique to improve the age of information over dense WLANs
Age of Information (AoI) is a relatively new metric introduced to capture the freshness of a
particular piece of information. While throughput and delay measurements are widely …
particular piece of information. While throughput and delay measurements are widely …
Deep reinforcement learning-based contention window optimization for IEEE 802.11 networks
This study focuses on optimizing the contention window (CW) in IEEE 802.11 networks
using deep reinforcement learning (DRL) to enhance the effectiveness of the contention …
using deep reinforcement learning (DRL) to enhance the effectiveness of the contention …
Dynamically Tuning IEEE 802.11's Contention Window Using Machine Learning
Y Edalat, K Obraczka - Proceedings of the 22nd international ACM …, 2019 - dl.acm.org
The IEEE 802.11's binary exponential backoff (BEB) algorithm plays a critical role in the
throughput performance and fair channel allocation of IEEE 802.11 networks. In particular …
throughput performance and fair channel allocation of IEEE 802.11 networks. In particular …
To buffer or not to buffer: IEEE 802.11 p/bd performance under different buffering strategies
A fundamental paradigm of the Internet of Things (IoT) consists of agents that communicate
updates to each other to perform joint actions, eg, cooperative awareness in transportation …
updates to each other to perform joint actions, eg, cooperative awareness in transportation …
Contention window optimization in IEEE 802.11 ax networks with deep reinforcement learning
W Wydmański, S Szott - 2021 IEEE wireless communications …, 2021 - ieeexplore.ieee.org
The proper setting of contention window (CW) values has a significant impact on the
efficiency of Wi-Fi networks. Unfortunately, the standard method used by 802.11 networks is …
efficiency of Wi-Fi networks. Unfortunately, the standard method used by 802.11 networks is …
OSCAR: A Contention Window Optimization Approach Using Deep Reinforcement Learning
C Grasso, R Raftopoulos… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
The contention window (CW) has a significant impact on the efficiency of Wi-Fi networks.
Unfortunately, the basic access method employed by 802.11 networks does not scale well …
Unfortunately, the basic access method employed by 802.11 networks does not scale well …
Matching while learning: Wireless scheduling for age of information optimization at the edge
In this paper, we investigate the minimization of age of information (AoI), a metric that
measures the information freshness, at the network edge with unreliable wireless …
measures the information freshness, at the network edge with unreliable wireless …