Zobrazit minimální záznam

dc.contributor.authorPham, Minh Nam
dc.contributor.authorDo, Dinh-Thuan
dc.contributor.authorNguyen, Tien Tung
dc.contributor.authorPhu, Tran Tin
dc.date.accessioned2018-01-25T07:00:31Z
dc.date.available2018-01-25T07:00:31Z
dc.date.issued2018
dc.identifier.citationTelecommunication Systems. 2018, vol. 67, issue 1, p. 123-132.cs
dc.identifier.issn1018-4864
dc.identifier.issn1572-9451
dc.identifier.urihttp://hdl.handle.net/10084/123378
dc.description.abstractWe consider spectrum-sharing scenario where coexist two communication networks including primary network and secondary network using the same spectrum. While the primary network includes directional multi-transceivers, the secondary network consists of relaying-based transceiver forwarding signals by energy harvesting assisted relay node. In cognitive radio, signals transmitted from secondary network are sufficiently small so that all of primary network receivers have signal to noise ratio (SNR) greater than a given threshold. In contrast, the transmitted signals from primary network cause increasing noise which is difficult to demodulate at secondary network nodes and hence it leads to the peak power constraint. In this paper, we focus on the influence of random location of transceivers at primary network using decode-and-forward protocol. Specifically, we derive closed-form outage probability expression of the secondary network under random location of transceivers and peak power constraint of primary network. This investigation shows the relationship between the fraction of energy harvesting time of time switching-based relaying protocol on outage probability of secondary network and throughput. In addition, we analyse the influence of the number of primary network transceivers as well as primary network's SNR threshold on secondary network. Furthermore, the trade-off between increasing energy harvesting and rate was investigated under the effect of energy conversion efficiency. The accuracy of the expressions is validated via Monte-Carlo simulations. Numerical results highlight the trade-offs associated with the various energy harvesting time allocations as a function of outage performance.cs
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofseriesTelecommunication Systemscs
dc.relation.urihttps://doi.org/10.1007/s11235-017-0325-0cs
dc.rights© Springer Science+Business Media New York 2017cs
dc.subjectenergy harvestingcs
dc.subjectcognitive radiocs
dc.subjectoutage probabilitycs
dc.subjectthroughputcs
dc.titleEnergy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysiscs
dc.typearticlecs
dc.identifier.doi10.1007/s11235-017-0325-0
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume67cs
dc.description.issue1cs
dc.description.lastpage132cs
dc.description.firstpage123cs
dc.identifier.wos000419707400010


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