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DQN-Based Adaptive Modulation Scheme Over Wireless Communication Channels
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Donggu | - |
| dc.contributor.author | Sun, Young Ghyu | - |
| dc.contributor.author | Kim, Soo Hyun | - |
| dc.contributor.author | Sim, Isaac | - |
| dc.contributor.author | Hwang, Yu Min | - |
| dc.contributor.author | Shin, Yoan | - |
| dc.contributor.author | Kim, Dong In | - |
| dc.contributor.author | Kim, Jin Young | - |
| dc.date.available | 2020-08-19T06:05:03Z | - |
| dc.date.created | 2020-08-18 | - |
| dc.date.issued | 2020-06 | - |
| dc.identifier.issn | 1089-7798 | - |
| dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/38445 | - |
| dc.description.abstract | In this letter, to improve data rate over wireless communication channels, we propose a deep Q network (DQN)-based adaptive modulation scheme by using Markov decision process (MDP) model. The proposed algorithm makes the reinforcement learning agent to select rate region boundaries as the states, which divide signal-to-noise ratio (SNR) range into rate regions. The simulation results show that spectral efficiency can be improved on the average by 0.5395 bps/Hz in wide SNR range. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
| dc.relation.isPartOf | IEEE COMMUNICATIONS LETTERS | - |
| dc.title | DQN-Based Adaptive Modulation Scheme Over Wireless Communication Channels | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1109/LCOMM.2020.2978390 | - |
| dc.type.rims | ART | - |
| dc.identifier.bibliographicCitation | IEEE COMMUNICATIONS LETTERS, v.24, no.6, pp.1289 - 1293 | - |
| dc.description.journalClass | 1 | - |
| dc.identifier.wosid | 000542942700031 | - |
| dc.identifier.scopusid | 2-s2.0-85086470333 | - |
| dc.citation.endPage | 1293 | - |
| dc.citation.number | 6 | - |
| dc.citation.startPage | 1289 | - |
| dc.citation.title | IEEE COMMUNICATIONS LETTERS | - |
| dc.citation.volume | 24 | - |
| dc.contributor.affiliatedAuthor | Shin, Yoan | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.subject.keywordAuthor | Modulation | - |
| dc.subject.keywordAuthor | Signal to noise ratio | - |
| dc.subject.keywordAuthor | Learning (artificial intelligence) | - |
| dc.subject.keywordAuthor | Adaptation models | - |
| dc.subject.keywordAuthor | Wireless communication | - |
| dc.subject.keywordAuthor | Adaptive systems | - |
| dc.subject.keywordAuthor | Neural networks | - |
| dc.subject.keywordAuthor | Adaptive modulation | - |
| dc.subject.keywordAuthor | deep learning | - |
| dc.subject.keywordAuthor | deep Q network | - |
| dc.subject.keywordAuthor | reinforcement learning | - |
| dc.relation.journalResearchArea | Telecommunications | - |
| dc.relation.journalWebOfScienceCategory | Telecommunications | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
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Related Researcher
- Shin, Yo an
- College of Information Technology (Department of IT Convergence)