Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined Radio
J Jagannath - Proceedings of the AAAI Symposium Series, 2024 - ojs.aaai.org
Abstract Machine learning promises to empower dynamic resource allocation requirements
of Next Generation (NextG) wireless networks including 6G and tactical networks. Recently …
of Next Generation (NextG) wireless networks including 6G and tactical networks. Recently …
Transfer Reinforcement Learning for Dynamic Spectrum Environment
H Sheng, W Zhou, J Zheng, Y Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reinforcement learning (RL) has proven to be an effective approach for achieving
intelligence in Cognitive Radio (CR). Through interactions with the environment, RL enables …
intelligence in Cognitive Radio (CR). Through interactions with the environment, RL enables …
When spectrum sharing in cognitive networks meets deep reinforcement learning: Architecture, fundamentals, and challenges
Next-generation wireless networks require the integration of cognitive networks (CNs) and
decision-making techniques to improve the spectrum efficiency. The conventional spectrum …
decision-making techniques to improve the spectrum efficiency. The conventional spectrum …
Cognitive network spectrum allocation based on multi-agent reinforcement learning
L Wang, L Zhang - Third International Conference on …, 2022 - spiedigitallibrary.org
A more important part of the field of deep reinforcement learning is the study of multi-agents,
for the specific scenario of multi-cognitive networks, the choice of spectrum will be affected …
for the specific scenario of multi-cognitive networks, the choice of spectrum will be affected …
Reinforcement learning based channel selection for design of routing protocol in cognitive radio network
Cognitive Radio Network (CRN) is a next generation of wireless communication technology
for efficient spectrum utilization. A cognitive Radio (CR) is able to recognize the idle …
for efficient spectrum utilization. A cognitive Radio (CR) is able to recognize the idle …
Throughput enhancement in a cognitive radio network using a reinforcement learning method
JC Clement, KC Sriharipriya, P Prakasam - Multimedia Tools and …, 2024 - Springer
As the demand for higher data rate is exponentially growing, spectral efficiency improving
methods can be adopted in recent day's wireless communication systems. If the cognitive …
methods can be adopted in recent day's wireless communication systems. If the cognitive …
Multi-agent Competitive Spectrum Handoff Based on Improved MADDPG Algorithm
L Shufeng, S Wei, P Yunfei, Z Min - 2021 IEEE 9th International …, 2021 - ieeexplore.ieee.org
Spectrum handoff plays an important role in realizing dynamic spectrum management.
When there are multiple competing secondary users (SUs) in a cognitive radio network, the …
When there are multiple competing secondary users (SUs) in a cognitive radio network, the …
Deep reinforcement learning for resource management in c-ran for dynamic environment
L Chen, M Murata - 2021 IEEE Globecom Workshops (GC …, 2021 - ieeexplore.ieee.org
The cloud radio access network (C-RAN) is a novel mobile network architecture that reduces
network design and operation costs and makes it easier to deploy large-scale networks …
network design and operation costs and makes it easier to deploy large-scale networks …
Reconfigurable intelligent surface enhanced cognitive radio networks
The cognitive radio (CR) network is a promising network architecture that meets the
requirement of enhancing scarce radio spectrum utilization. Meanwhile, reconfigurable …
requirement of enhancing scarce radio spectrum utilization. Meanwhile, reconfigurable …
Multi-antenna tuning simulation platform by deep reinforcement learning
Y Zhao, K Zhang, R Han - 2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
Recently, communication technology is highly developed. The communication convenience
that people enjoy is relying on a large number of base station antenna devices set up by …
that people enjoy is relying on a large number of base station antenna devices set up by …