Next Article in Journal
Nonsmooth Levenberg-Marquardt Type Method for Solving a Class of Stochastic Linear Complementarity Problems with Finitely Many Elements
Previous Article in Journal
Cross-Coupled Contouring Control of Multi-DOF Robotic Manipulator
Article Menu

Export Article

Open AccessArticle
Algorithms 2016, 9(4), 82; doi:10.3390/a9040082

Linear Algorithms for Radioelectric Spectrum Forecast

1
Faculty of Technology, Universidad Distrital Francisco José de Caldas, Bogota 110231, Colombia
2
Industrial and Systems Engineering Department, Faculty of Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia
3
Electrical Engineering Department, Universidad Autónoma Metropolitana Iztapalapa, Mexico City 09340, Mexico
*
Author to whom correspondence should be addressed.
Academic Editor: Javier Del Ser Lorente
Received: 2 August 2016 / Revised: 25 October 2016 / Accepted: 28 November 2016 / Published: 2 December 2016
View Full-Text   |   Download PDF [5765 KB, uploaded 2 December 2016]   |  

Abstract

This paper presents the development and evaluation of two linear algorithms for forecasting reception power for different channels at an assigned spectrum band of global systems for mobile communications (GSM), in order to analyze the spatial opportunity for reuse of frequencies by secondary users (SUs) in a cognitive radio (CR) network. The algorithms employed correspond to seasonal autoregressive integrated moving average (SARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), which allow for a forecast of channel occupancy status. Results are evaluated using the following criteria: availability and occupancy time for channels, different types of mean absolute error, and observation time. The contributions of this work include a more integral forecast as the algorithm not only forecasts reception power but also the occupancy and availability time of a channel to determine its precision percentage during the use by primary users (PUs) and SUs within a CR system. Algorithm analyses demonstrate a better performance for SARIMA over GARCH algorithm in most of the evaluated variables. View Full-Text
Keywords: cognitive radio; time series; linear algorithms cognitive radio; time series; linear algorithms
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Pedraza, L.F.; Hernandez, C.A.; Paez, I.P.; Ortiz, J.E.; Rodriguez-Colina, E. Linear Algorithms for Radioelectric Spectrum Forecast. Algorithms 2016, 9, 82.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top