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Cooperative Multi-Agent Learning and Coordination for Cognitive Radio Networks
2014
IEEE Journal on Selected Areas in Communications
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Cognitive radio networks require coordination of secondary stations with primary stations (so that secondary stations should not interfere with primary stations) and of secondary stations with each other ...
As it is whenever stations share resources, coordination is a central issue in cognitive radio networks: absent coordination, there may be collision, congestion or interference, with concomitant loss of ...
Both single-agent and multi-agent learning play a role in the existing literature on cognitive radio networks. ...
doi:10.1109/jsac.2014.140308
fatcat:o67pzgfqgvalfgawgidrxemuwy
On Using Multi Agent Systems in Cognitive Radio Networks: A Survey
2012
International Journal of Wireless & Mobile Networks
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We propose among others a classification of cognitive radio proposals based on multi-agent concept and point out the pros and cons for each of the described approach. ...
This paper presents a state of the art on cognitive radio researches especially works using multi-agent systems. ...
ACKNOWLEDGEMENTS This work is partly supported by the Ministry of Higher Education and Research of France. ...
doi:10.5121/ijwmn.2012.4601
fatcat:3wvhimw4pjamlpqfmbv5wwncte
Cooperative Multi-Agent Reinforcement Learning Based Distributed Dynamic Spectrum Access in Cognitive Radio Networks
[article]
2021
arXiv
pre-print
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on cooperative multi-agent reinforcement learning (MARL). ...
In this paper, we investigate the distributed DSA problem for multi-user in a typical multi-channel cognitive radio network. ...
The QMIX is accommodated for multi-agent cooperative settings, in which the agents achieve the optimal strategy by coordinating with each other. ...
arXiv:2106.09274v1
fatcat:cb5767uktrespkeoqmsvh2bxpq
A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks
2013
International Journal of Communication Networks and Information Security
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radio networks is presented. ...
The idea of Cognitive Radio (CR) is to share the spectrum between a user called primary, and a user called secondary. ...
It is this capacity to communicate, to coordinate and to cooperate which makes interesting the use of agents in cognitive radio networks. ...
dblp:journals/ijcnis/BenmammarAK13
fatcat:bjeduqtkwra5nn3vb5mfdoa3ku
Cognitive and cooperative wireless networks
[chapter]
2012
The Newcom++ Vision Book
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These events culminated in the creation of the IEEE 802.22, developing a cognitive radio-based physical and medium access control layer for use by license-exempt devices on a non-interfering basis in spectrum ...
revolutions in the wireless networks for the next decades, since it completely breaks the way how spectrum has been traditionally managed. ...
More specifically to docition, scalability is a problem for many learning techniques and especially for multi-agent learning. ...
doi:10.1007/978-88-470-1983-6_4
fatcat:cngxb7rv3nct3icecvoogrp6uy
IEEE TCCN Special Section Editorial: Evolution of Cognitive Radio to AI-Enabled Radio and Networks
2020
IEEE Transactions on Cognitive Communications and Networking
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In the multi-agent learning process, the PUs and SUs learn strategies to maximize their benefits and improve spectrum utilization. ...
Finally, the last article, "Market-Based Model in CR-IoT: A Q-Probabilistic Multi-agent Reinforcement Learning Approach", by Wang et al., proposes a multi-agent reinforcement learning (MARL) algorithm ...
doi:10.1109/tccn.2020.2975440
fatcat:lofvpltbibcwvnpfqaivkh7eyq
Intelligent Wireless Communication System Using Cognitive Radio
2012
International Journal of Distributed and Parallel systems
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In this paper, we present a state of the art on the use of Multi Agent Systems (MAS) for spectrum access using cooperation and competition to solve the problem of spectrum allocation and ensure better ...
Then we propose a new approach which uses the CR for improving wireless communication for a single cognitive radio mobile terminal (CRMT). ...
MULTI AGENT SYSTEMS AND COGNITIVE RADIO The association of MAS and the CR can provide a great future for the optimal management of frequencies (in comparison with the rigid control techniques proposed ...
doi:10.5121/ijdps.2012.3208
fatcat:5xdqvoxu6zffbphbyatavpkvpq
Recent advances on artificial intelligence and learning techniques in cognitive radio networks
2015
EURASIP Journal on Wireless Communications and Networking
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, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. ...
For efficient real-time process, the cognitive radio is usually combined with artificial intelligence and machine-learning techniques so that an adaptive and intelligent allocation is achieved. ...
The author relied on game and multi-agent Q-learning in order to create his model. Mir et al. in [92] used a multi-agent system for dynamic spectrum sharing in cognitive radio networks. ...
doi:10.1186/s13638-015-0381-7
fatcat:dq6aba75obc5vlxnbaqrerlsii
BENS−B5G: Blockchain-Enabled Network Slicing in 5G and Beyond-5G (B5G) Networks
2022
Sensors
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The intrinsic qualities of a blockchain, which has lately acquired prominence, mean that it is critical for the 5G network and B5G networks. ...
the radio access network (RAN) schedule, to guarantee that their end-to-end services are effortlessly executed. ...
We have utilized multi-agent reinforcement learning for cooperative power distribution in CRNs. ...
doi:10.3390/s22166068
pmid:36015829
pmcid:PMC9415280
fatcat:enfdo25rpzb3jd3c2rtbpmxi3e
Cognitive networks with trainable adaptive radio systems
2011
Procedia Computer Science
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In this study, a new method is proposed for establishing and managing cognitive wireless networks with the help of trainable and adaptive radio systems. ...
Cognitive networks enable users to focus on the content and context rather than configuration and management of the networks. ...
Fujii and Suzuki [12] proposed a novel multi-band routing method for cognitive radio using ad-hoc networks. ...
doi:10.1016/j.procs.2010.12.122
fatcat:zxeedumxurggbejnc6teyrd5vy
Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning
[article]
2018
arXiv
pre-print
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In this paper, we discuss the development of the cognitive radio technology and machine learning techniques and emphasize their roles in improving spectrum and energy utility of wireless communication ...
We also present practical applications of these techniques and identify further research challenges in cognitive radio and machine learning as applied to the existing and future wireless communication ...
A distributed multi-agent multi-band reinforcement learning framework is developed in [153] for spectrum sensing in ad hoc cognitive radio networks. ...
arXiv:1710.11240v4
fatcat:elt77cgcxvappbxvspp7evb74u
Sensing time and power allocation for cognitive radios using distributed Q-learning
2012
EURASIP Journal on Wireless Communications and Networking
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Cognitive radios are established in two steps: the radios firstly sense the available frequency bands and secondly communicate using these bands. ...
In this article, we propose two decentralized resource allocation Q-learning algorithms: the first one is used to share the sensing time among the cognitive radios in a way that maximize the throughputs ...
However, multi-agent Q-learning algorithms have been successfully applied in multiple scenarios [11] and in particular to cognitive radios [10, 12, 19] . ...
doi:10.1186/1687-1499-2012-138
fatcat:eohizpq6v5gfvbspu2faoemcpy
20 Years of Evolution from Cognitive to Intelligent Communications
[article]
2019
arXiv
pre-print
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Particularly, this article starts from a comprehensive review of typical spectrum sensing and sharing, followed by the recent achievements on the AI-enabled intelligent radio. ...
It has been regarded as the key enabler for intelligent communications. ...
[105] have proposed a multi-agent Q-learning algorithm to avoid the interference in self-organized femtocell networks. ...
arXiv:1909.11562v1
fatcat:au2oewpfm5eb3ccnnpvrcbypim
Bayesian Sequential Learning for Railway Cognitive Radio
2019
Promet (Zagreb)
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Then, based on the available environmental information, we propose a multi-cognitive-base-station cascade collaboration algorithm by using naive Bayesian learning and agent theory. ...
This cognitive-base-station multi-agent system scheme comprehensively solves the problem of low efficiency in the dynamic access of the railway cognitive radio. ...
MAC protocols in cognitive radio ad hoc networks In [22, 23] , the MAC protocol in the cognitive radio network generally has the functions of spectrum management, equipment coordination and power control ...
doi:10.7307/ptt.v31i2.2934
fatcat:f27lyw2narcqvkvy74smdfyw4a
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning
[article]
2020
arXiv
pre-print
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As examples, we propose neighborhood cognition consistent deep Q-learning and Actor-Critic to facilitate large-scale multi-agent cooperations. ...
Inspired by these observations, we take the first step to introduce neighborhood cognitive consistency (NCC) into multi-agent reinforcement learning (MARL). ...
Acknowledgments The authors would like to thank Jun Qian, Dong Chen and Min Cheng for partial engineering support. The authors would also like to thank the anonymous reviewers for their comments. ...
arXiv:1912.01160v2
fatcat:gpdrinhignfzxieci56zfcqkiq
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