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Article: Cache-Enabling UAV Communications: Network Deployment and Resource Allocation

TitleCache-Enabling UAV Communications: Network Deployment and Resource Allocation
Authors
KeywordsEdge caching
resource allocation
UAV deployment
user association
Issue Date2020
Citation
IEEE Transactions on Wireless Communications, 2020, v. 19, n. 11, p. 7470-7483 How to Cite?
AbstractIn this article, we investigate the content distribution in the hotspot area, whose traffic is offloaded by the combination of the unmanned aerial vehicle (UAV) communication and edge caching. In cache-enabling UAV-assisted cellular networks, the network deployment and resource allocation are vital for quality of experience (QoE) of users with content distribution applications. We formulate a joint optimization problem of UAV deployment, caching placement and user association for maximizing QoE of users, which is evaluated by mean opinion score (MOS). To solve this challenging problem, we decompose the optimization problem into three sub-problems. Specifically, we propose a swap matching based UAV deployment algorithm, then obtain the near-optimal caching placement and user association by greedy algorithm and Lagrange dual, respectively. Finally, we propose a low complexity iterative algorithm for the joint UAV deployment, caching placement and user association optimization problem, which achieves good computational complexity-optimality tradeoff. Simulation results reveal that: i) the MOS of the proposed algorithm approaches that of the exhaustive search method and converges within several iterations; and ii) compared with the benchmark algorithms, the proposed algorithm achieves better performance in terms of MOS, content access delay and backhaul traffic offloading.
Persistent Identifierhttp://hdl.handle.net/10722/349485
ISSN
2023 Impact Factor: 8.9
2023 SCImago Journal Rankings: 5.371

 

DC FieldValueLanguage
dc.contributor.authorZhang, Tiankui-
dc.contributor.authorWang, Yi-
dc.contributor.authorLiu, Yuanwei-
dc.contributor.authorXu, Wenjun-
dc.contributor.authorNallanathan, Arumugam-
dc.date.accessioned2024-10-17T06:58:50Z-
dc.date.available2024-10-17T06:58:50Z-
dc.date.issued2020-
dc.identifier.citationIEEE Transactions on Wireless Communications, 2020, v. 19, n. 11, p. 7470-7483-
dc.identifier.issn1536-1276-
dc.identifier.urihttp://hdl.handle.net/10722/349485-
dc.description.abstractIn this article, we investigate the content distribution in the hotspot area, whose traffic is offloaded by the combination of the unmanned aerial vehicle (UAV) communication and edge caching. In cache-enabling UAV-assisted cellular networks, the network deployment and resource allocation are vital for quality of experience (QoE) of users with content distribution applications. We formulate a joint optimization problem of UAV deployment, caching placement and user association for maximizing QoE of users, which is evaluated by mean opinion score (MOS). To solve this challenging problem, we decompose the optimization problem into three sub-problems. Specifically, we propose a swap matching based UAV deployment algorithm, then obtain the near-optimal caching placement and user association by greedy algorithm and Lagrange dual, respectively. Finally, we propose a low complexity iterative algorithm for the joint UAV deployment, caching placement and user association optimization problem, which achieves good computational complexity-optimality tradeoff. Simulation results reveal that: i) the MOS of the proposed algorithm approaches that of the exhaustive search method and converges within several iterations; and ii) compared with the benchmark algorithms, the proposed algorithm achieves better performance in terms of MOS, content access delay and backhaul traffic offloading.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Wireless Communications-
dc.subjectEdge caching-
dc.subjectresource allocation-
dc.subjectUAV deployment-
dc.subjectuser association-
dc.titleCache-Enabling UAV Communications: Network Deployment and Resource Allocation-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TWC.2020.3011881-
dc.identifier.scopuseid_2-s2.0-85095521372-
dc.identifier.volume19-
dc.identifier.issue11-
dc.identifier.spage7470-
dc.identifier.epage7483-
dc.identifier.eissn1558-2248-

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