Deep Learning Based Resource Assignment for Wireless Networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Minseok | - |
dc.contributor.author | Lee, Hoon | - |
dc.contributor.author | Lee, Hongju | - |
dc.contributor.author | Lee, Inkyu | - |
dc.date.accessioned | 2022-02-13T10:41:10Z | - |
dc.date.available | 2022-02-13T10:41:10Z | - |
dc.date.created | 2022-01-20 | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 1089-7798 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/135614 | - |
dc.description.abstract | This letter studies a deep learning approach for binary assignment problems in wireless networks, which identifies binary variables for permutation matrices. This poses challenges in designing a structure of a neural network and its training strategies for generating feasible assignment solutions. To this end, this letter develop a new Sinkhorn neural network which learns a non-convex projection task onto a set of permutation matrices. An unsupervised training algorithm is proposed where the Sinkhorn neural network can be applied to network assignment problems. Numerical results demonstrate the effectiveness of the proposed method in various network scenarios. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Deep Learning Based Resource Assignment for Wireless Networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Inkyu | - |
dc.identifier.doi | 10.1109/LCOMM.2021.3116233 | - |
dc.identifier.scopusid | 2-s2.0-85118657745 | - |
dc.identifier.wosid | 000728924700031 | - |
dc.identifier.bibliographicCitation | IEEE COMMUNICATIONS LETTERS, v.25, no.12, pp.3888 - 3892 | - |
dc.relation.isPartOf | IEEE COMMUNICATIONS LETTERS | - |
dc.citation.title | IEEE COMMUNICATIONS LETTERS | - |
dc.citation.volume | 25 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 3888 | - |
dc.citation.endPage | 3892 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Cost function | - |
dc.subject.keywordAuthor | Deep learning | - |
dc.subject.keywordAuthor | Deep learning | - |
dc.subject.keywordAuthor | Neural networks | - |
dc.subject.keywordAuthor | Sinkhorn operator | - |
dc.subject.keywordAuthor | Supervised learning | - |
dc.subject.keywordAuthor | Task analysis | - |
dc.subject.keywordAuthor | Training | - |
dc.subject.keywordAuthor | Wireless networks | - |
dc.subject.keywordAuthor | assignment problem | - |
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