Title:
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Implications of decentralized Q-learning resource allocation in wireless networks
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Author:
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Wilhelmi Roca, Francesc; Bellalta, Boris; Cano Bastidas, Cristina; Jonsson, Anders, 1973-
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Abstract:
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Comunicació presentada al 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), celebrat els dies 8 a 13 d'octubre de 2017 a Montreal, Canadà. |
Abstract:
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Reinforcement Learning is gaining attention by the wireless networking community due to its potential to learn good-performing configurations only from the observed results. In this work we propose a stateless variation of Q-learning, which we apply to exploit spatial reuse in a wireless network. In particular, we allow networks to modify both their transmission power and the channel used solely based on the experienced throughput. We concentrate in a completely decentralized scenario in which no information about neighbouring nodes is available to the learners. Our results show that although the algorithm is able to find the best-performing actions to enhance aggregate throughput, there is high variability in the throughput experienced by the individual networks. We identify the cause of this variability as the adversarial setting of our setup, in which the most played actions provide intermittent good/poor performance depending on the neighbouring decisions. We also evaluate the effect of the intrinsic learning parameters of the algorithm on this variability. |
Abstract:
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This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502), and by the European Regional Development Fund under grant TEC2015-71303-R (MINECO/FEDER). |
Subject(s):
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-Throughput -Aggregates -Interference -Resource management -Meters -Signal to noise ratio -Wireless networks |
Rights:
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© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The final published article can be found at http://ieeexplore.ieee.org/document/8292321/ |
Document type:
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Conference Object Article - Accepted version |
Published by:
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Institute of Electrical and Electronics Engineers (IEEE)
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