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dc.contributor.authorZhou, Jiusi
dc.contributor.authorDang, Shuping
dc.contributor.authorShihada, Basem
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2020-10-18T10:45:10Z
dc.date.available2020-10-18T10:45:10Z
dc.date.issued2020
dc.identifier.citationZhou, J., Dang, S., Shihada, B., & Alouini, M.-S. (2020). Power Allocation for Relayed OFDM with Index Modulation Assisted by Artificial Neural Network. IEEE Wireless Communications Letters, 1–1. doi:10.1109/lwc.2020.3031638
dc.identifier.issn2162-2345
dc.identifier.doi10.1109/LWC.2020.3031638
dc.identifier.urihttp://hdl.handle.net/10754/665614
dc.description.abstractIn this letter, we propose a power allocation scheme for relayed orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. The proposed power allocation scheme replies on artificial neural network (ANN) and deep learning to allocate transmit power among various subcarriers at the source and relay nodes. The objective of the power allocation scheme is to minimize the overall transmit power under a set of constraints. Without loss of generality, we assume all subcarriers at source and relay nodes are independently distributed with different statistical distribution parameters. The relay node adopts the fixed-gain amplify-and-forward (FG AF) relaying protocol. We employ the adaptive moment estimation method (Adam) to implement back-propagation learning and simulate the proposed power allocation scheme. The analytical and simulation results show that the proposed power allocation scheme is able to provide comparable performance as the optimal solution but with lower complexity.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9226618/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9226618
dc.rights(c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.subjectPower allocation
dc.subjectindex modulation
dc.subjectOFDM
dc.subjectamplify-and-forward relaying
dc.subjectartificial neural network (ANN).
dc.titlePower Allocation for Relayed OFDM with Index Modulation Assisted by Artificial Neural Network
dc.typeArticle
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentNetworks Laboratory (NetLab)
dc.identifier.journalIEEE Wireless Communications Letters
dc.eprint.versionPost-print
dc.identifier.pages1-1
dc.identifier.arxivid2010.12959
kaust.personZhou, Jiusi
kaust.personDang, Shuping
kaust.personShihada, Basem
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2020-10-18T10:47:54Z


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