Thirty years of machine learning: The road to Pareto-optimal wireless networks
Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …
complex compelling applications both in military and civilian fields, where the users are able …
Deep reinforcement learning: An overview
Y Li - arXiv preprint arXiv:1701.07274, 2017 - arxiv.org
We give an overview of recent exciting achievements of deep reinforcement learning (RL).
We discuss six core elements, six important mechanisms, and twelve applications. We start …
We discuss six core elements, six important mechanisms, and twelve applications. We start …
Spectrum sensing for cognitive radio: Recent advances and future challenge
Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to
diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth …
diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth …
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 …
Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …
decision strategies. However, in many cases, it is desirable to learn directly from …
Supervised machine learning techniques in cognitive radio networks during cooperative spectrum handovers
H Anandakumar, K Umamaheswari - Cluster Computing, 2017 - Springer
Cognitive communication model perform the investigation and surveillance of spectrum in
cognitive radio networks abetment in advertent primary users (PUs) and in turn help in …
cognitive radio networks abetment in advertent primary users (PUs) and in turn help in …
Cognitive radio for smart grids: Survey of architectures, spectrum sensing mechanisms, and networking protocols
AA Khan, MH Rehmani… - … Surveys & Tutorials, 2015 - ieeexplore.ieee.org
Traditional power grids are currently being transformed into smart grids (SGs). SGs feature
multi-way communication among energy generation, transmission, distribution, and usage …
multi-way communication among energy generation, transmission, distribution, and usage …
Dynamic spectrum sharing in 5G wireless networks with full-duplex technology: Recent advances and research challenges
Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same
frequency band at the same time, and it is considered to be one of the candidate …
frequency band at the same time, and it is considered to be one of the candidate …
Spectrum inference in cognitive radio networks: Algorithms and applications
Spectrum inference, also known as spectrum prediction in the literature, is a promising
technique of inferring the occupied/free state of radio spectrum from already …
technique of inferring the occupied/free state of radio spectrum from already …
Recent advances on artificial intelligence and learning techniques in cognitive radio networks
Cognitive radios are expected to play a major role towards meeting the exploding traffic
demand over wireless systems. A cognitive radio node senses the environment, analyzes …
demand over wireless systems. A cognitive radio node senses the environment, analyzes …