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dc.contributor.authorKazıklı, Ertanen_US
dc.contributor.authorDulek, Berkanen_US
dc.contributor.authorGezici, Sinanen_US
dc.date.accessioned2020-02-05T10:52:40Z
dc.date.available2020-02-05T10:52:40Z
dc.date.issued2019-05
dc.identifier.issn1536-1276
dc.identifier.urihttp://hdl.handle.net/11693/53086
dc.description.abstractIn this paper, modulation classification and symbol decoding problems are jointly considered and optimal strategies are proposed under various settings. In the considered framework, there exist a number of candidate modulation formats and the aim is to decode a sequence of received signals with an unknown modulation scheme. To that aim, two different formulations are proposed. In the first formulation, the prior probabilities of the modulation schemes are assumed to be known and a formulation is proposed under the Bayesian framework. This formulation takes a constrained approach in which the objective function is related to symbol decoding performance whereas the constraint is related to modulation classification performance. The second formulation, on the other hand, addresses the case in which the prior probabilities of the modulation schemes are unknown, and provides a method under the minimax framework. In this case, a constrained approach is employed as well; however, the introduced performance metrics differ from those in the first formulation due to the absence of the prior probabilities of the modulation schemes. Finally, the performance of the proposed methods is illustrated through simulations. It is demonstrated that the proposed techniques improve the introduced symbol detection performance metrics via relaxing the constraint(s) on the modulation classification performance compared with the conventional techniques in a variety of system configurations.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE Transactions on Wireless Communicationsen_US
dc.relation.isversionofhttps://doi.org/ 10.1109/TWC.2019.2906185en_US
dc.subjectModulation classificationen_US
dc.subjectDemodulationen_US
dc.subjectBayesen_US
dc.subjectMinimaxen_US
dc.titleOptimal joint modulation classification and symbol decodingen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage2623en_US
dc.citation.epage2638en_US
dc.citation.volumeNumber18en_US
dc.citation.issueNumber5en_US
dc.identifier.doi10.1109/TWC.2019.2906185en_US
dc.publisherIEEEen_US
dc.contributor.bilkentauthorKazıklı, Ertan
dc.contributor.bilkentauthorDulek, Berkan
dc.contributor.bilkentauthorGezici, Sinan
dc.identifier.eissn1558-2248


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