SPECTRAL VACANCIES PREDICTION METHOD FOR COGNITIVE RADIO APPLICATIONS

Authors

  • A. Canavitsas
  • L. da Silva Mello

DOI:

https://doi.org/10.1590/2179-10742016v15i1581

Keywords:

Spectral vacancies, spectrum sharing, cognitive radio

Abstract

Cognitive radio technology is in fast development and is considered a possible solution to improve the efficiency of radio spectrum use. Many studies have been recently carried out in order to improve spectrum-sharing techniques between primary and secondary users. This paper investigates one of the basic decision problems faced by a cognitive radio: given a time window of a specific size, a secondary user (SU) should decide if it will use it or not, minimizing the chances of collision with a primary user (PU). For this purpose, an algorithm is proposed that does not require previous information about PU occupancy behavior.  The proposed algorithm shows very good performance when compared to three other methods recently proposed to tackle with this problem.

References

[1] Thomas G., Fast detection of spectral white spaces for cognitive radio networks IEEE MILCOM 2009,
Univ. of Louisiana at Lafayette, Lafayette, LA, USA - October, 2009.
[2] Canavitsas A., da Silva Mello L., Grivet M. Spectrum Occupation Modeling on the 450 MHz Band for
Cognitive Radios Application. EUCAP 2013 - Gothenburg, Sweden - April, 2013.
[3] Soleimani T., Azad Q., Kahvand M., Sarikhani, R. Handoff reduction based on prediction approach in
Cognitive Radio Networks ICCT 2013, - Guilin, China - Nov. 2013
[4] Silverman, S.J. Game Theory and Software Define Radios, Military Communication Conference, 2006 –
MILCOM 2006, IEEE.
[5] Jing T, Xing X, Cheng W, Huo Y., Cooperative spectrum prediction in multi-PU multi-SU cognitive radio
networks. ICCR 2013 - Beijing, China - Nov. 2013
[6] Akhtar, A.N., Rashdi, A., Arif, F., Fusion Based Spectrum Decision Framework for Cognitive Radio Users
- Mobile and Multimedia Networks (WoWMoM), 2015 IEEE 16th International Symposium on a World of
Wireless - Boston, MA – USA
[7] Barnes S.D., Maharaj M.T., Prediction based channel allocation performance for cognitive radio.
International Journal of Electronics and Communications pp.336-345 Volume 68, Issue 4, April 2014.
[8] Zhao Z., Wang L.l, Ding G., Wei S., Enhanced Spectrum Decision Based on the Combination of Sensing
and Prediction - Cross Strait Quad-Regional Radio Science and Wireless Technology Conference
(CSQRWC), 2011 – Harbin - China
[9] Gulnur S., Uyanik, Canberk B., Oktug S., Predictive Spectrum Decision Mechanisms in Cognitive. Radio
Networks GC’12 Workshop: Ad Hoc Networking with MIMO and Cognitive Radio, - Anaheim, California,
USA - Dec. 2012.
[10]Gulnur S., Oktug S.A., QoS Based Cooperative Spectrum Utilization in Cognitive Radio Networks, Sarnoff
Symposium (SARNOFF), 2012 35th IEEE, Newark, NJ – USA
[11]Cox D.R., Principles of Statistical Inference, Cambridge University Press, 2006.
[12]Maharjan S., Takada K., Experimental Study of Energy Detector Prototype for Cognitive Radio System.
IEICE Technical Report, SR-2007-52(2007-11), Hiroshima International University, Hiroshima, Japan.
[13]Kim J., Jeffrey A., Sensitive White Space Detection with Spectral Covariance Sensing. IEEE Transactions
on Wireless Communications, Vol. 9, No. 9, September 2010.
[14]Canavitsas A., da Silva Mello L., Grivet M., White space prediction technique for cognitive radio
applications Microwave & Optoelectronics Conference (IMOC), 2013 SBMO/IEEE MTT-S International,
Rio de Janeiro, Brazil.

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Published

2016-08-01

How to Cite

A. Canavitsas, & L. da Silva Mello. (2016). SPECTRAL VACANCIES PREDICTION METHOD FOR COGNITIVE RADIO APPLICATIONS. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 15(1), 18 - 29. https://doi.org/10.1590/2179-10742016v15i1581

Issue

Section

Regular Papers