detección de espectro para radio cognitiva spectrum sensing for cognitive radio
Clicks: 179
ID: 226146
2012
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
179 views
25 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #26 of 42 articles by views in international journal of electrical and computer engineering
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Este artículo centra su atención en la capa física de las redes de radio cognitiva (CR), es decir, en las técnicas que se utilizan para detectar la presencia o ausencia de usuarios licenciados en las diferentes bandas del espectro electromagnético. Las técnicas presentadas, con sus ventajas y desventajas, están organizadas jerárquicamente como: técnicas fundamentales (detección de energía, filtro adaptado y características ciclo-estacionarias), técnicas basadas en las fundamentales o evolución (detección de forma de onda, identificación del radiotransmisor, detección de la potencia de fuga en el receptor) y técnicas alternativas típicas del análisis de imágenes (transformada Hough y Wavelet). Adicionalmente se describen los retos principales en la detección de usuarios licenciados junto con las diferentes dimensiones en las que se pueden hallar oportunidades de uso espectral eficiente por parte de los dispositivos de radio cognitiva.
This survey article focuses on the physical layer for cognitive radio (CR) networks, namely the techniques to detect the presence/absence of licensed users in the different spectrum bands. The techniques presented in this article, including their advantages and disadvantages, are organized in a hierarchical fashion as follows: fundamental detection techniques (energy-based detection, matched filter, and cyclostationarity features), fundamental-detection-based techniques (waveform detection, radio identification, local-oscillator leakage power), and alternative techniques that are typical of the image analysis domain (Hough and Wavelet transforms). Additionally, the main challenges associated to licensed user detection are described together with the various spectral dimensions where cognitive radio devices can find new spectrum opportunities.
This survey article focuses on the physical layer for cognitive radio (CR) networks, namely the techniques to detect the presence/absence of licensed users in the different spectrum bands. The techniques presented in this article, including their advantages and disadvantages, are organized in a hierarchical fashion as follows: fundamental detection techniques (energy-based detection, matched filter, and cyclostationarity features), fundamental-detection-based techniques (waveform detection, radio identification, local-oscillator leakage power), and alternative techniques that are typical of the image analysis domain (Hough and Wavelet transforms). Additionally, the main challenges associated to licensed user detection are described together with the various spectral dimensions where cognitive radio devices can find new spectrum opportunities.
| Reference Key |
pedraza2012ingeniaredeteccin
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Luis Fernando Pedraza;Felipe Forero;Ingrid Patricia Páez |
| Journal | international journal of electrical and computer engineering |
| Year | 2012 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.