A Reinforcement Learning Based Low-Delay Scheduling with Adaptive Transmission
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhao, Yu | - |
dc.contributor.author | Lee, Joohyun | - |
dc.date.accessioned | 2021-06-22T11:01:35Z | - |
dc.date.available | 2021-06-22T11:01:35Z | - |
dc.date.created | 2021-01-22 | - |
dc.date.issued | 2019-10 | - |
dc.identifier.issn | 2162-1233 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/4550 | - |
dc.description.abstract | As modern communication systems become indispensable, the requirements for communication systems such as delay and power get more stringent. In this paper, we adopt a Reinforcement Learning (RL) based approach to obtain the optimal trade-off between delay and power consumption for a given power constraint in a communication system whose conditions (e.g., channel conditions, traffic arrival rates) can change over time. To this end, we first formulate this problem as an infinite-horizon Markov Decision Process (MDP) and then Q-learning is adopted to solve this problem. To handle the given power constraint, we apply the Lagrange multiplier method that transforms a constrained optimization problem into a non-constrained problem. Finally, via simulation, we show that Q-learning achieves the optimal policy. © 2019 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | A Reinforcement Learning Based Low-Delay Scheduling with Adaptive Transmission | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Joohyun | - |
dc.identifier.doi | 10.1109/ICTC46691.2019.8939680 | - |
dc.identifier.scopusid | 2-s2.0-85078234256 | - |
dc.identifier.wosid | 000524690200210 | - |
dc.identifier.bibliographicCitation | ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, pp.916 - 919 | - |
dc.relation.isPartOf | ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future | - |
dc.citation.title | ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future | - |
dc.citation.startPage | 916 | - |
dc.citation.endPage | 919 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | Constrained optimization | - |
dc.subject.keywordPlus | Economic and social effects | - |
dc.subject.keywordPlus | Lagrange multipliers | - |
dc.subject.keywordPlus | Learning algorithms | - |
dc.subject.keywordPlus | Machine learning | - |
dc.subject.keywordPlus | Markov processes | - |
dc.subject.keywordPlus | Adaptive transmission | - |
dc.subject.keywordPlus | Channel conditions | - |
dc.subject.keywordPlus | Constrained optimi-zation problems | - |
dc.subject.keywordPlus | delay-power tradeoff | - |
dc.subject.keywordPlus | Infinite horizons | - |
dc.subject.keywordPlus | Lagrange multiplier method | - |
dc.subject.keywordPlus | Markov Decision Processes | - |
dc.subject.keywordPlus | Power constraints | - |
dc.subject.keywordPlus | Reinforcement learning | - |
dc.subject.keywordAuthor | adaptive transmission | - |
dc.subject.keywordAuthor | delay-power tradeoff | - |
dc.subject.keywordAuthor | infinite-horizon Markov Decision Process | - |
dc.subject.keywordAuthor | Reinforcement Learning | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8939680/ | - |
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