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dc.contributor.authorBenkhelifa, Fatma
dc.contributor.authorElSawy, Hesham
dc.contributor.authorMcCann, Julie A.
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2020-01-26T10:44:58Z
dc.date.available2020-01-26T10:44:58Z
dc.date.issued2020
dc.identifier.citationBenkhelifa, F., ElSawy, H., Mccann, J. A., & Alouini, M.-S. (2020). Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study. IEEE Transactions on Wireless Communications, 19(4), 2699–2712. doi:10.1109/twc.2020.2967697
dc.identifier.doi10.1109/TWC.2020.2967697
dc.identifier.urihttp://hdl.handle.net/10754/661150
dc.description.abstractThis paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvesting energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the buffers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modelled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of the data buffers and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission success probability from buffers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which define the network parameters that ensure stable network operation and finite packet delay. Furthermore, the spatially averaged network performance, in terms of transmission success probability, average queueing delay, and average queue size are investigated. For self-sustainable networks, the results quantify the required buffer size and packet delay, which are crucial for the design of IoT devices and time critical IoT applications.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8968738/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8968738
dc.relation.urlhttp://spiral.imperial.ac.uk/bitstream/10044/1/76842/8/FINAL%20VERSION.pdf
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.rightsThis file is an open access version redistributed from: http://spiral.imperial.ac.uk/bitstream/10044/1/76842/8/FINAL%20VERSION.pdf
dc.subjectSpatiotemporal models
dc.subjectstochastic geometry
dc.subjectqueueing theory
dc.subjectenergy harvesting
dc.subjectpacket transmission success probability
dc.subjecttwo-dimensional discrete-time Markov chain
dc.subjectstability conditions
dc.titleRecycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study
dc.typeArticle
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalIEEE Transactions on Wireless Communications
dc.eprint.versionPost-print
dc.contributor.institutionImperial College London, London SW7 2AZ, United Kingdom.
dc.contributor.institutionKing Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2020-12-02T12:50:24Z
dc.date.published-online2020-01-24
dc.date.published-print2020-04


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