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dc.contributor.authorYang, Hong-Chuan
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2019-04-28T13:14:35Z
dc.date.available2019-04-28T13:14:35Z
dc.date.issued2018-05-24
dc.identifier.urihttp://hdl.handle.net/10754/632533
dc.description.abstractThe growing popularity of big data and Internet of Things (IoT) applications bring new challenges to the wireless communication community. Wireless transmission systems should more efficiently support the large amount of data traffics from diverse types of information sources. In this article, we introduce a novel data-oriented approach for the design and optimization of wireless transmission strategies. Specifically, we define new performance metrics for individual data transmission session and apply them to compare two popular channel-adaptive transmission strategies. We develop several interesting and somewhat counterintuitive observations on these transmission strategies, which would not be possible with conventional approach. We also present several interesting future research directions that are worth pursuing with the data-oriented approach.
dc.publisherarXiv
dc.relation.urlhttp://arxiv.org/abs/1805.09923v1
dc.relation.urlhttp://arxiv.org/pdf/1805.09923v1
dc.rightsArchived with thanks to arXiv
dc.titleWireless Transmission of Big Data: Data-Oriented Performance Limits and Their Applications
dc.typePreprint
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.eprint.versionPre-print
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
dc.identifier.arxivid1805.09923
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2019-04-29T06:24:03Z


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