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dc.contributor.authorShen, C.en_US
dc.contributor.authorZhou, R.en_US
dc.contributor.authorTekin, Cemen_US
dc.contributor.authorSchaar, M. V. D.en_US
dc.date.accessioned2019-02-21T16:04:37Z
dc.date.available2019-02-21T16:04:37Z
dc.date.issued2018en_US
dc.identifier.issn1932-4553
dc.identifier.urihttp://hdl.handle.net/11693/50198
dc.description.abstractMotivated by the engineering problem of cellular coverage optimization, we propose a novel multiarmed bandit model called generalized global bandit. We develop a series of greedy algorithms that have the capability to handle nonmonotonic but decomposable reward functions, multidimensional global parameters, and switching costs. The proposed algorithms are rigorously analyzed under the multiarmed bandit framework, where we show that they achieve bounded regret, and hence, they are guaranteed to converge to the optimal arm in finite time. The algorithms are then applied to the cellular coverage optimization problem to achieve the optimal tradeoff between sufficient small cell coverage and limited macroleakage without prior knowledge of the deployment environment. The performance advantage of the new algorithms over existing bandits solutions is revealed analytically and further confirmed via numerical simulations. The key element behind the performance improvement is a more efficient 'trial and error' mechanism, in which any trial will help improve the knowledge of all candidate power levels.
dc.description.sponsorshipManuscript received July 14, 2017; revised October 30, 2017; accepted January 15, 2018. Date of publication January 25, 2018; date of current version February 16, 2018. The work of C. Shen and R. Zhou was supported by the National Natural Science Foundation of China under Grant 61572455 and Grant 61631017. The work of C. Tekin was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under 3501 Program Grant 116E229. The work of M. van der Schaar was supported by the National Science Foundation under Grant 1407712 and Grant 1533983. The guest editor coordinating the review of this paper and approving it for publication was Prof. H. Vincent Poor. (Corresponding author: Cong Shen.) C. Shen and R. Zhou are with the School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China (e-mail: congshen@ustc.edu.cn; zrd127@mail.ustc.edu.cn).
dc.language.isoEnglish
dc.source.titleIEEE Journal on Selected Topics in Signal Processingen_US
dc.relation.isversionofhttps://doi.org/10.1109/JSTSP.2018.2798164
dc.subjectCoverage optimizationen_US
dc.subjectMulti-armed banditen_US
dc.subjectOnline learningen_US
dc.subjectRegret analysisen_US
dc.titleGeneralized global bandit and its application in cellular coverage optimizationen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage218en_US
dc.citation.epage232en_US
dc.citation.volumeNumber12en_US
dc.citation.issueNumber1en_US
dc.relation.projectNational Science Foundation, NSF: 1407712 - National Science Foundation, NSF: 1533983 - University of Science and Technology of China, USTC: zrd127@mail.ustc.edu.cn - 116E229 - Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK - National Natural Science Foundation of China, NSFC: 61631017 - National Natural Science Foundation of China, NSFC: 61572455
dc.identifier.doi10.1109/JSTSP.2018.2798164
dc.publisherInstitute of Electrical and Electronics Engineers
dc.contributor.bilkentauthorTekin, Cemen_US


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