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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F14%3APU110395%21RIV15-MSM-26220___
rdf:type
n7:Vysledek skos:Concept
dcterms:description
Deploying new wireless systems is very difficult in the current system of frequency spectrum assignments. The most prospective spectrum bands are fixed allocated for specific services and these bands are controlled by national telecommunication (governmental) organizations. Measurements of the frequency spectrum background show that a huge underutilization of the frequency spectrum exists. Overall effectiveness of spectrum utilization is widely discussed in the context of cognitive radio and dynamic spectrum allocation. An autonomous and intelligent system should improve spectrum sharing capabilities by detecting current, licensed users – primary users with established connections in unused spectrum bands for cognitive radio – and secondary users. In this paper, a machine learning algorithm is used and channels in particular bands are scored according to a weight function. Real measured data are used as frequency spectrum background. This system should decrease interference in communication channe Deploying new wireless systems is very difficult in the current system of frequency spectrum assignments. The most prospective spectrum bands are fixed allocated for specific services and these bands are controlled by national telecommunication (governmental) organizations. Measurements of the frequency spectrum background show that a huge underutilization of the frequency spectrum exists. Overall effectiveness of spectrum utilization is widely discussed in the context of cognitive radio and dynamic spectrum allocation. An autonomous and intelligent system should improve spectrum sharing capabilities by detecting current, licensed users – primary users with established connections in unused spectrum bands for cognitive radio – and secondary users. In this paper, a machine learning algorithm is used and channels in particular bands are scored according to a weight function. Real measured data are used as frequency spectrum background. This system should decrease interference in communication channe
dcterms:title
Rapid Channel Assignment for Intelligent Indoor Scenarios Rapid Channel Assignment for Intelligent Indoor Scenarios
skos:prefLabel
Rapid Channel Assignment for Intelligent Indoor Scenarios Rapid Channel Assignment for Intelligent Indoor Scenarios
skos:notation
RIV/00216305:26220/14:PU110395!RIV15-MSM-26220___
n3:aktivita
n5:P
n3:aktivity
P(ED2.1.00/03.0072)
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
n19:1487248 n19:7942311
n3:druhVysledku
n10:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
41349
n3:idVysledku
RIV/00216305:26220/14:PU110395
n3:jazykVysledku
n9:eng
n3:klicovaSlova
cognitive radio, spectrum measurement, spectrum allocation, dynamic spectrum access
n3:klicoveSlovo
n4:dynamic%20spectrum%20access n4:spectrum%20measurement n4:cognitive%20radio n4:spectrum%20allocation
n3:kontrolniKodProRIV
[F2A33814FEF0]
n3:mistoKonaniAkce
The Hague
n3:mistoVydani
Neuveden
n3:nazevZdroje
The 8th European Conference on Antennas and Propagation (EuCAP 2014)
n3:obor
n18:JA
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n17:ED2.1.00%2F03.0072
n3:rokUplatneniVysledku
n11:2014
n3:tvurceVysledku
Vlachová Hutová, Eliška Urban, Robert
n3:typAkce
n16:WRD
n3:zahajeniAkce
2014-04-06+02:00
s:numberOfPages
3
n12:hasPublisher
Neuveden
n15:isbn
978-88-907018-4-9
n13:organizacniJednotka
26220