Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/17748
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Comsa, IS | - |
dc.contributor.author | Zhang, S | - |
dc.contributor.author | Aydin, ME | - |
dc.contributor.author | Kuonen, P | - |
dc.contributor.author | Lu, Y | - |
dc.contributor.author | Trestian, R | - |
dc.contributor.author | Ghinea, G | - |
dc.date.accessioned | 2019-03-20T14:21:27Z | - |
dc.date.available | 2018-12-01 | - |
dc.date.available | 2019-03-20T14:21:27Z | - |
dc.date.issued | 2018-08-06 | - |
dc.identifier.citation | IEEE Transactions on Network and Service Management, 2018, 15 (4), pp. 1661 - 1675 | en_US |
dc.identifier.issn | http://dx.doi.org/10.1109/TNSM.2018.2863563 | - |
dc.identifier.issn | 1932-4537 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/17748 | - |
dc.description.sponsorship | European Union | en_US |
dc.format.extent | 1661 - 1675 | - |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | 5G | en_US |
dc.subject | Packet Scheduling | en_US |
dc.subject | Optimization | en_US |
dc.subject | Radio Resource Management | en_US |
dc.subject | Reinforcement Learning | en_US |
dc.subject | Neural Networks | en_US |
dc.title | Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/TNSM.2018.2863563 | - |
dc.relation.isPartOf | IEEE Transactions on Network and Service Management | - |
pubs.issue | 4 | - |
pubs.publication-status | Published | - |
pubs.volume | 15 | - |
dc.identifier.eissn | 1932-4537 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
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FullText.pdf | 4.99 MB | Adobe PDF | View/Open |
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