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Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/13023
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dc.contributor.authorJose, Justinen_US
dc.contributor.authorBhatia, Vimalen_US
dc.date.accessioned2024-01-09T06:33:16Z-
dc.date.available2024-01-09T06:33:16Z-
dc.date.issued2023-
dc.identifier.citationJose, J., Agarwal, A., Shaik, P., Goyal, V., Choi, K., & Bhatia, V. (2023). Performance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Network. IEEE Systems Journal. Scopus. https://doi.org/10.1109/JSYST.2023.3331123en_US
dc.identifier.issn1932-8184-
dc.identifier.otherEID(2-s2.0-85179809893)-
dc.identifier.urihttps://doi.org/10.1109/JSYST.2023.3331123-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/13023-
dc.description.abstractThis work investigates a device-to-device (D2D) underlayed cellular system where both D2D and cellular networks are NOMA enabled, which is not only more spectrally efficient than the previous D2D and NOMA models but also can outperform them. Specifically, we first present closed-form expressions for system outage probability (SOP) and sum ergodic rate (SER) metrics for performance analysis and thereafter propose a deep neural network-based power control mechanism for SOP minimization. Analytical results are validated with extensive simulations that reveal the effectiveness of the proposed model over comparative schemes and the requirement of optimizing the power values in accordance with change in different system parameters. IEEEen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceIEEE Systems Journalen_US
dc.subjectDecodingen_US
dc.subjectDevice-to-device communicationen_US
dc.subjectFading channelsen_US
dc.subjectInterference cancellationen_US
dc.subjectNakagami-m fadingen_US
dc.subjectNOMAen_US
dc.subjectnonorthogonal multiple access (NOMA)en_US
dc.subjectoutage probabilityen_US
dc.subjectProtocolsen_US
dc.subjectSymbolsen_US
dc.titlePerformance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Networken_US
dc.typeJournal Articleen_US
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