HF spectrum activity prediction model based on HMM for cognitive radio applications

Melián Gutiérrez, Laura and Zazo Bello, Santiago and Blanco Murillo, José Luis and Pérez Álvarez, Iván and García Rodríguez, Adrián José and Pérez Díaz, Baltasar (2012). HF spectrum activity prediction model based on HMM for cognitive radio applications. "Physical Communication" ; pp. 1-13. ISSN 1874-4907. https://doi.org/10.1016/j.phycom.2012.09.004.

Description

Title: HF spectrum activity prediction model based on HMM for cognitive radio applications
Author/s:
  • Melián Gutiérrez, Laura
  • Zazo Bello, Santiago
  • Blanco Murillo, José Luis
  • Pérez Álvarez, Iván
  • García Rodríguez, Adrián José
  • Pérez Díaz, Baltasar
Item Type: Article
Título de Revista/Publicación: Physical Communication
Date: November 2012
ISSN: 1874-4907
Subjects:
Freetext Keywords: Cognitive radio; HF; Hidden Markov model; Prediction
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

More information

Item ID: 16774
DC Identifier: http://oa.upm.es/16774/
OAI Identifier: oai:oa.upm.es:16774
DOI: 10.1016/j.phycom.2012.09.004
Official URL: http://www.sciencedirect.com/science/article/pii/S1874490712000742#
Deposited by: Memoria Investigacion
Deposited on: 10 Aug 2013 08:10
Last Modified: 01 Dec 2014 23:56
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