Energy Efficiency Analysis of Collaborative Compressive Sensing for Cognitive Radio Networks

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dc.contributor.VIAF113149196515374792028 (Al-Dhahir, N)
dc.contributor.authorKishore, R.
dc.contributor.authorGurugopinath, S.
dc.contributor.authorMuhaidat, S.
dc.contributor.authorSofotasios, P. C.
dc.contributor.authorDianati, M.
dc.contributor.authorAl-Dhahir, Naofal
dc.contributor.utdAuthorAl-Dhahir, Naofal
dc.date.accessioned2019-11-08T23:52:18Z
dc.date.available2019-11-08T23:52:18Z
dc.date.created2019-12-09
dc.descriptionDue to copyright restrictions full text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).
dc.description.abstractWe investigate the energy efficiency of a conventional collaborative compressed sensing (CCCS) scheme in cognitive radio networks. In particular, we derive expressions for the throughput, energy consumption and energy efficiency, and analyze the trade-off between the achievable throughput and the energy consumption of the underlying CCCS scheme. Furthermore, we formulate a multiple variable non-convex optimization problem to determine the optimum compression level that maximizes the energy efficiency, subject to interference constraints. We propose a sub-optimal solution based on tight approximations to simplify the aforementioned optimization problem, and further demonstrate that the energy efficiency achieved by the CCCS scheme is higher than that of conven- tional collaborative sensing scheme, under the same predefined conditions. It is further shown that the increase in the energy efficiency of CCCS scheme is due to the considerable decrease in the energy consumption, which is particularly noticeable with a large number of sensors. © 2018 IEEE.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.identifier.bibliographicCitationKishore, R., S. Gurugopinath, S. Muhaidat, P. C. Sofotasios, et al. 2019. "Energy Efficiency Analysis of Collaborative Compressive Sensing for Cognitive Radio Networks." 2018 IEEE Global Communications Conference (GLOBECOM), doi: 10.1109/GLOCOM.2018.8647779
dc.identifier.isbn9781538647271
dc.identifier.urihttps://hdl.handle.net/10735.1/7102
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.isPartOf2018 IEEE Global Communications Conference (GLOBECOM)
dc.relation.urihttps://dx.doi.org/10.1109/GLOCOM.2018.8647779
dc.rights©2018 IEEE
dc.subjectDetectors
dc.subjectEnergy consumption
dc.subjectCognitive radio networks
dc.subjectConvex programming
dc.titleEnergy Efficiency Analysis of Collaborative Compressive Sensing for Cognitive Radio Networks
dc.type.genrearticle

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