Communication efficient channel estimation over distributed networks

dc.citation.epage142en_US
dc.citation.spage138en_US
dc.contributor.authorSayın, Muhammed O.en_US
dc.contributor.authorVanlı, N. Denizcanen_US
dc.contributor.authorGöze, T.en_US
dc.contributor.authorKozat, Süleyman Serdaren_US
dc.coverage.spatialAtlanta, GA, USAen_US
dc.date.accessioned2016-02-08T12:26:15Z
dc.date.available2016-02-08T12:26:15Z
dc.date.issued2014en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 3-5 December 2014en_US
dc.descriptionConference Name: GlobalSIP 2014: 2nd IEEE Global Conference on Signal and Information Processing, IEEE 2014en_US
dc.description.abstractWe study diffusion based channel estimation in distributed architectures suitable for various communication applications such as cognitive radios. Although the demand for distributed processing is steadily growing, these architectures require a substantial amount of communication among their nodes (or processing elements) causing significant energy consumption and increase in carbon footprint. Due to growing awareness of telecommunication industry's impact on the environment, the need to mitigate this problem is indisputable. To this end, we introduce algorithms significantly reducing the communication load between distributed nodes, which is the main cause in energy consumption, while providing outstanding performance. In this framework, after each node produces its local estimate of the communication channel, a single bit or a couple of bits of information is generated using certain random projections. This newly generated data is diffused and then used in neighboring nodes to recover the original full information, i.e., the channel estimate of the desired communication channel. We provide the complete state-space description of these algorithms and demonstrate the substantial gains through our experiments.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:26:15Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2014en
dc.identifier.doi10.1109/GlobalSIP.2014.7032094en_US
dc.identifier.urihttp://hdl.handle.net/11693/28652
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/GlobalSIP.2014.7032094en_US
dc.source.titleProceedings of the GlobalSIP 2014: 2nd IEEE Global Conference on Signal and Information Processing, IEEE 2014en_US
dc.subjectCarbon footprinten_US
dc.subjectCognitive radioen_US
dc.subjectCommunication channels (information theory)en_US
dc.subjectNetwork architectureen_US
dc.subjectTelecommunication industryen_US
dc.subjectCommunication applicationen_US
dc.subjectDiffusion based channelsen_US
dc.subjectDistributed architectureen_US
dc.subjectDistributed networksen_US
dc.subjectDistributed processingen_US
dc.subjectImpact on the environmenten_US
dc.subjectProcessing elementsen_US
dc.subjectState-space descriptionen_US
dc.subjectChannel estimationen_US
dc.titleCommunication efficient channel estimation over distributed networksen_US
dc.typeConference Paperen_US

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