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dc.contributor.authorAli, Konpal S.*
dc.contributor.authorHaenggi, Martin*
dc.contributor.authorElsawy, Hesham*
dc.contributor.authorChaaban, Anas*
dc.contributor.authorAlouini, Mohamed-Slim*
dc.date.accessioned2018-04-04T12:38:14Z
dc.date.available2018-04-04T12:38:14Z
dc.date.issued2018-03-21en
dc.identifier.urihttp://hdl.handle.net/10754/627405.1
dc.description.abstractA network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\mathcal{R}_{\rm tot}$, for general $N$, constrained to: 1) a minimum rate $\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\mathcal{R}_{\rm tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\mathcal{R}_{\rm tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.en
dc.publisherarXiven
dc.relation.urlhttp://arxiv.org/abs/1803.07866v1en
dc.relation.urlhttp://arxiv.org/pdf/1803.07866v1en
dc.rightsArchived with thanks to arXiven
dc.titleDownlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networksen
dc.typePreprinten
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division*
dc.contributor.departmentElectrical Engineering Program*
dc.eprint.versionPre-printen
dc.contributor.institutionDepartment of Electrical Engineering, University of Notre Dame, USA.*
dc.identifier.arxividarXiv:1803.07866en
kaust.personAli, Konpal S.
kaust.personElsawy, Hesham
kaust.personChaaban, Anas
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2018-06-14T03:58:17Z


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