Rapid Channel Assignment for Intelligent Indoor Scenarios

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU110395" target="_blank" >RIV/00216305:26220/14:PU110395 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Rapid Channel Assignment for Intelligent Indoor Scenarios

Popis výsledku v původním jazyce

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 channels efficiently and increase data throughput with minimal costs. A further significant reduction of radiation power should be obtained by spectrum efficient communication. Smart buildings represent a great opportunity for this type of cognitive system.

Název v anglickém jazyce

Rapid Channel Assignment for Intelligent Indoor Scenarios

Popis výsledku anglicky

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 channels efficiently and increase data throughput with minimal costs. A further significant reduction of radiation power should be obtained by spectrum efficient communication. Smart buildings represent a great opportunity for this type of cognitive system.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/ED2.1.00%2F03.0072" target="_blank" >ED2.1.00/03.0072: Centrum senzorických, informačních a komunikačních systémů (SIX)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

ISBN

978-88-907018-4-9

ISSN

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e-ISSN

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Počet stran výsledku

3

Strana od-do

907-910

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

The Hague

Datum konání akce

6. 4. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000361548800205