Reinforcement Learning-based Wi-Fi Contention Window Optimization
SCS Cruz, MA Ouameur, FAP de Figueiredo - 2022 - preprints.org
The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal.
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
Reinforcement learning-based Wi-Fi contention window optimization
SJ Sheila de Cássia, MA Ouameur… - Journal of …, 2023 - jcis.emnuvens.com.br
The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal.
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
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 …
Enhancing IEEE 802.11 Standard with Deep Reinforcement Learning for Optimal Channel Access
SCDSJ Cruz, FAP de Figueiredo… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
According to IEEE 802.11 standard, the collision avoidance mechanism is not the most
efficient as it relies on a binary exponential backoff (BEB) algorithm. This algorithm …
efficient as it relies on a binary exponential backoff (BEB) algorithm. This algorithm …
[HTML][HTML] Cfx: contention-free channel access for IEEE 802.11 ax
K Lee, D Kim - Sensors, 2022 - mdpi.com
Orthogonal frequency-division multiple access (OFDMA) has attracted great attention as a
key technology for uplink enhancement for Wi-Fi, since it can effectively reduce network …
key technology for uplink enhancement for Wi-Fi, since it can effectively reduce network …
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 …
Applying deep reinforcement learning to improve throughput and reduce collision rate in IEEE 802.11 networks
Abstract The effectiveness of Wi-Fi networks is greatly influenced by the optimization of
contention window (CW) parameters. Unfortunately, the conventional approach employed …
contention window (CW) parameters. Unfortunately, the conventional approach employed …
[HTML][HTML] Wireless LAN performance enhancement using double deep Q-networks
K Asaf, B Khan, GY Kim - Applied Sciences, 2022 - mdpi.com
Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage
pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access …
pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access …
Deep Reinforcement Learning for Optimizing Restricted Access Window in IEEE 802.11 ah MAC Layer
The IEEE 802.11 ah standard is introduced to address the growing scale of internet of things
(IoT) applications. To reduce contention and enhance energy efficiency in the system, the …
(IoT) applications. To reduce contention and enhance energy efficiency in the system, the …
A Hierarchical Deep Learning Approach for Optimizing CCA Threshold and Transmit Power in Wi-Fi Networks
The nodes, eg, access points and clients, in current WiFi networks rely on carrier sense
multiple access (CSMA) for channel access. This means they rely on a clear channel …
multiple access (CSMA) for channel access. This means they rely on a clear channel …