Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning
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 …
position in providing Internet access thanks to their freedom of deployment and configuration …
Optimizing with low budgets: A comparison on the black-box optimization benchmarking suite and openai gym
The growing ubiquity of machine learning (ML) has led it to enter various areas of computer
science, including black-box optimization (BBO). Recent research is particularly concerned …
science, including black-box optimization (BBO). Recent research is particularly concerned …
DAI-NET: Toward communication-aware collaborative training for the industrial edge
The industrial edge generates an abundance of spatially distributed and dynamic data that
needs to remain on-site for privacy and security reasons. Collaborative training at the edge …
needs to remain on-site for privacy and security reasons. Collaborative training at the edge …
Rfrl gym: A reinforcement learning testbed for cognitive radio applications
D Rosen, I Rochez, C McIrvin, J Lee… - arXiv preprint arXiv …, 2023 - arxiv.org
Radio Frequency Reinforcement Learning (RFRL) is anticipated to be a widely applicable
technology in the next generation of wireless communication systems, particularly 6G and …
technology in the next generation of wireless communication systems, particularly 6G and …
Snout: A middleware platform for software-defined radios
JK Becker, D Starobinski - IEEE Transactions on Network and …, 2022 - ieeexplore.ieee.org
The plethora of Internet of Things (IoT) protocols and the upcoming availability of new
spectrum bands for wirelessly connected devices have made software-defined radio (SDR) …
spectrum bands for wirelessly connected devices have made software-defined radio (SDR) …
Low-budget Black-box Optimization Algorithms Evaluated on BBOB and OpenAI Gym
The growing ubiquity of machine learning (ML) has led it to enter various areas of computer
science, including black-box optimization (BBO). Recent research is particularly concerned …
science, including black-box optimization (BBO). Recent research is particularly concerned …
Grgym: A playground for research on rl/ai enhanced wireless networks
A Zubow, S Roesler, P Gawlowicz… - … Wireless 2022; 27th …, 2022 - ieeexplore.ieee.org
The provision of a wide range of services each with different requirements makes next
generation wireless networks become more complex and heterogeneous which is aimed to …
generation wireless networks become more complex and heterogeneous which is aimed to …
[HTML][HTML] DRLLA: Deep Reinforcement Learning for Link Adaptation
Link adaptation (LA) matches transmission parameters to conditions on the radio link, and
therefore plays a major role in telecommunications. Improving LA is within the requirements …
therefore plays a major role in telecommunications. Improving LA is within the requirements …
prisma-v2: Extension to Cloud Overlay Networks
RA Alliche, TDS Barros… - 2023 23rd …, 2023 - ieeexplore.ieee.org
In this paper, we present prisma-v2, a new release of prisma, a Packet Routing Simulator for
Multi-Agent Reinforcement Learning. prisma-v2 brings a new set of features. First, it allows …
Multi-Agent Reinforcement Learning. prisma-v2 brings a new set of features. First, it allows …
IoT security and privacy assessment using software-defined radios
JK Becker - 2022 - search.proquest.com
Abstract The Internet of Things (IoT) has seen exceptional adoption in recent years, resulting
in an unprecedented level of connectivity in personal and industrial domains. In parallel …
in an unprecedented level of connectivity in personal and industrial domains. In parallel …