Aprendizaje profundo por refuerzo aplicado al control de acceso en redes IEEE 802.11.

F Frommel Araújo - 2022 - lareferencia.info
En estos últimos tiempos, las tecnologías de la información y la comunicación, apalancadas
por la masificación en el acceso a internet, han modificado el comercio, la educación, el …

Applying deep reinforcement learning to improve throughput and reduce collision rate in IEEE 802.11 networks

CH Ke, L Astuti - KSII Transactions on Internet and Information …, 2022 - koreascience.kr
Abstract The effectiveness of Wi-Fi networks is greatly influenced by the optimization of
contention window (CW) parameters. Unfortunately, the conventional approach employed …

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 …

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 …

Deep reinforcement learning-based contention window optimization for IEEE 802.11 networks

YH Tu, YW Ma, CH Ke - 2024 - researchsquare.com
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 …

Deep Reinforcement Learning for Optimizing Restricted Access Window in IEEE 802.11 ah MAC Layer

X Jiang, S Gong, C Deng, L Li, B Gu - Sensors, 2024 - mdpi.com
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 …

Decentralized Deep Reinforcement Learning Approach for Channel Access Optimization

SC da SJ Cruz, FAP de Figueiredo, RAA de Souza - 2024 - researchsquare.com
Abstract The IEEE 802.11 standard's binary exponential back-off (BEB) algorithm is the
prevailing method for tackling the collision avoidance problem. Under the BEB paradigm …

Decentralized Deep Reinforcement Learning Approach for Channel Access Optimization

C SCdSJ, FAP de Figueiredo, RAA de Souza - 2024 - europepmc.org
The IEEE 802.11 standard's binary exponential back-off (BEB) algorithm is the prevailing
method for tackling the collision avoidance problem. Under the BEB paradigm, the back-off …

[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 …

SmartLA: Reinforcement learning-based link adaptation for high throughput wireless access networks

R Karmakar, S Chattopadhyay… - Computer Communications, 2017 - Elsevier
High throughput wireless standards based on IEEE 802.11 n and IEEE 802.11 ac have been
developed and released within the last few years as new amendments over the …