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 …
A three-tier deep learning-based channel access method for WiFi networks
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 …
capacity. Such a method must consider 1) channel bonding, which improves the …
A deep Q-network approach to optimize spatial reuse in WiFi networks
The proliferation of IEEE 802.11 or WiFi networks, and the explosive growth in traffic
demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the …
demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the …
ReinWiFi: A Reinforcement-Learning-Based Framework for the Application-Layer QoS Optimization of WiFi Networks
In this paper, a reinforcement-learning-based scheduling framework is proposed and
implemented to optimize the application-layer quality-of-service (QoS) of a practical wireless …
implemented to optimize the application-layer quality-of-service (QoS) of a practical wireless …
Bandwidth-Delay-Product-Based ACK Optimization Strategy for QUIC in Wi-Fi Networks
Y Liu, Z Yang, Y Peng, T Bi… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
QUIC has drawn extensive attention in supporting low latency and secure Internet of Things
(IoT) communications due to its efficient handshake and default end-to-end encryption …
(IoT) communications due to its efficient handshake and default end-to-end encryption …
A federated reinforcement learning framework for link activation in multi-link Wi-Fi networks
R Ali, B Bellalta - … IEEE International Black Sea Conference on …, 2023 - ieeexplore.ieee.org
Next-generation Wi-Fi networks are looking forward to introducing new features like multi-
link operation (MLO) to both achieve higher throughput and lower latency. However, given …
link operation (MLO) to both achieve higher throughput and lower latency. However, given …
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 …
Federated Deep Reinforcement Learning-Based Intelligent Channel Access in Dense Wi-Fi Deployments
X Du, X Fang, R He, L Yan, L Lu, C Luo - arXiv preprint arXiv:2409.01004, 2024 - arxiv.org
The IEEE 802.11 MAC layer utilizes the Carrier Sense Multiple Access with Collision
Avoidance (CSMA/CA) mechanism for channel contention and access. However, in densely …
Avoidance (CSMA/CA) mechanism for channel contention and access. However, in densely …
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 …
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 …