Analytical performance of soft data fusion-aided spectrum sensing in hybrid terrestrial-satellite networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU120984" target="_blank" >RIV/00216305:26220/16:PU120984 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1002/sat.1200" target="_blank" >http://dx.doi.org/10.1002/sat.1200</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/sat.1200" target="_blank" >10.1002/sat.1200</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analytical performance of soft data fusion-aided spectrum sensing in hybrid terrestrial-satellite networks

Popis výsledku v původním jazyce

The cognitive radio (CR) technology is developed to help secondary users to utilize spectrum holes of the primary users (PUs) opportunistically. Accurate detection of spectrum holes via cooperative spectrum sensing (CSS) is essential for realization of CR protocols in next generation hybrid terrestrial-satellite networks. Soft data fusion refers to a class of efficient CSS schemes for CR networks to find presence or absence of a PU. Each CR user senses the PU and transmits its sensing information in terms of energy obtained using energy detector to fusion center (FC). Next, any of the soft data schemes, which differ in technique of combining the energy information, may be performed at FC to acquire a final decision about a PU. In the present paper, numerical analysis of various soft data-aided CSS schemes in different fading/shadowing environments is studied. In particular, closed-form expressions of detection probability for the known soft data schemes are derived for each of the popular fading models. A comparative performance of soft combining schemes is illustrated for various network and channel conditions. Further, an optimal detection threshold that minimizes the total error is also indicated for different soft schemes.

Název v anglickém jazyce

Analytical performance of soft data fusion-aided spectrum sensing in hybrid terrestrial-satellite networks

Popis výsledku anglicky

The cognitive radio (CR) technology is developed to help secondary users to utilize spectrum holes of the primary users (PUs) opportunistically. Accurate detection of spectrum holes via cooperative spectrum sensing (CSS) is essential for realization of CR protocols in next generation hybrid terrestrial-satellite networks. Soft data fusion refers to a class of efficient CSS schemes for CR networks to find presence or absence of a PU. Each CR user senses the PU and transmits its sensing information in terms of energy obtained using energy detector to fusion center (FC). Next, any of the soft data schemes, which differ in technique of combining the energy information, may be performed at FC to acquire a final decision about a PU. In the present paper, numerical analysis of various soft data-aided CSS schemes in different fading/shadowing environments is studied. In particular, closed-form expressions of detection probability for the known soft data schemes are derived for each of the popular fading models. A comparative performance of soft combining schemes is illustrated for various network and channel conditions. Further, an optimal detection threshold that minimizes the total error is also indicated for different soft schemes.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING

ISSN

1542-0973

e-ISSN

1542-0981

Svazek periodika

99

Číslo periodika v rámci svazku

PP

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

19

Strana od-do

1-19

Kód UT WoS článku

000411328500005

EID výsledku v databázi Scopus

2-s2.0-85002611239