About: A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems
Creator	Ahmad, Bashar Tarczynski, Andrzej
topic	covid:df36ea5a235a42dde7cdbc618e4159d888ddba07#this
Source	PMC
abstract	This paper introduces a novel method of spectrum sensing in communication systems that utilizes nonuniform sampling in conjunction with a suitable spectral analysis tool. It is referred to here as spectral analysis for randomized sampling (SARS). Owing to the deployment of nonuniform sampling, the proposed technique can accomplish the sensing task by using sampling rates well below the ones demanded by uniform-sampling-based digital signal processing (DSP). The effect of the cyclostationary nature of the incoming digital communication signal on the adequacy of the adopted periodogram-type estimator for the spectrum sensing operation is addressed. The statistical characteristics of the estimator are presented. General reliability conditions on the length of the required signal observation window, i.e., sensing time, for a chosen sampling rate or vice versa are provided amid a sought system performance. The impact of the presence of noise and processing transmissions with various power levels on the derived dependability recommendations is given. The analytical results are illustrated by numerical examples. This paper establishes a new framework for efficient spectrum sensing where considerable savings on the sampling rate and number of processed samples can be attained.
has issue date	2011-08-15(xsd:dateTime)
bibo:doi	10.1109/tsp.2011.2165060
bibo:pmid	32391117
has license	cc-by
sha1sum (hex)	df36ea5a235a42dde7cdbc618e4159d888ddba07
schema:url	https://doi.org/10.1109/tsp.2011.2165060
resource representing a document's title	A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems
has PubMed Central identifier	PMC7176468
has PubMed identifier	32391117
schema:publication	IEEE Trans Signal Process
resource representing a document's body	covid:df36ea5a235a42dde7cdbc618e4159d888ddba07#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/df36ea5a235a42dde7cdbc618e4159d888ddba07
is schema:about of	named entity 'PROPOSED' named entity 'DIGITAL' named entity 'TASK' named entity 'OBSERVATION' named entity 'SAMPLING RATE' named entity 'HERE' named entity 'GIVEN' named entity 'UNIFORM' named entity 'ADEQUACY' named entity 'COMMUNICATION' named entity 'EFFICIENT' named entity 'RATES' named entity 'WSS signals' named entity 'seismology' named entity 'noise power' named entity 'DASP' named entity 'sampling rate' named entity 'unnormalised' named entity 'Parseval's theorem' named entity 'spectral analysis' named entity 'in-phase' named entity 'chi-squared distribution' named entity 'sampling-based algorithm' named entity 'autocorrelation function' named entity 'sampling rates' named entity 'sampling rate' named entity 'Fourier transform' named entity 'sampling rates' named entity 'sampling rate' named entity 'communication systems' named entity 'sampling' named entity 'SARS' named entity 'sampling rate' named entity 'digital signal processing' named entity 'spectral analysis' named entity 'SARS' named entity 'signal processing' named entity 'astronomy' named entity 'cyclostationary' named entity '1, 2' named entity 'variance reduction' named entity 'correlation' named entity 'radio spectrum' named entity 'spectral analysis' named entity 'sampling rates' named entity 'sampling rate' named entity 'ieee' named entity 'variance' named entity 'DASP' named entity 'discrete-time' named entity 'IEEE' named entity 'WSS signals' named entity 'Chebychev's inequality' named entity 'central limit theorem' named entity 'signal to noise ratio' named entity 'variance' named entity 'cyclostationary' named entity 'cyclostationarity' named entity 'integer' named entity 'feature detecting' named entity 'hypothesis testing' named entity 'cyclostationarity' named entity 'uncorrelated' named entity 'SARS' named entity 'DASP' named entity 'bandpass' named entity 'cyclostationary' named entity 'complex variable' named entity 'false alarm' named entity 'independent random variables' named entity 'IEEE' named entity 'bandpass' named entity 'sampling rate' named entity 'variance' named entity 'sampling rate' named entity 'sampling rates' named entity 'sampling rate' named entity '2, 3'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software