Distributed Power Control for Cognitive Satellite Networks

Article Preview

Abstract:

In this paper, we considered the problem of distributed power control for cognitive satellite networks. We defined a utility function that measures the user’s satisfaction, as a function of signal to interference plus noise ratio. And then a distributed power control algorithm was proposed based on the defined utility function. This algorithm can guarantee the protection of the primary user and meet quality of service requirements of the cognitive users. Simulation results show the performance of the proposed power control algorithm.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 490-495)

Pages:

1156-1160

Citation:

Online since:

March 2012

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Federal Communications Commission. Spectrum Policy Task Force. Report ET Docket, No. 02-135, Nov. (2002).

Google Scholar

[2] R.W. Broderson, A. Wolisz, D. Cabric, et al. CORVUS: A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum. White Paper submitted at the University of Berkeley, CA, July (2004).

Google Scholar

[3] J. Mitola and G.Q. Maguire. Cognitive Radio: Making Software Radio More Personal. Personal Communications, IEEE, 6 (1999) 13-18.

DOI: 10.1109/98.788210

Google Scholar

[4] J. Mitola. Cognitive Radio: An Integrated agent architecture for software defined radio. PhD Dissertation, Royal Inst. Technol. (KTH), Stockholm, Sweden, (2000).

Google Scholar

[5] S. Haykin. Cognitive Radio: Brain-Empowered Wireless Communications. IEEE Journal of Selected Areas in Communications, 23 (2005) 201-220.

DOI: 10.1109/jsac.2004.839380

Google Scholar

[6] J.T. Le and Q. Liang. An Efficient Power Control Scheme for Cognitive Radios. IEEE Journal of Selected Aeras in Communicaitons, 23 (2005)201-220.

Google Scholar

[7] W. Wang, T. Peng and W. Wang. Optimal Power Control Under Interference Temperature Constraint in Cognitive Radio Network. IEEE Wireless Communications and Networking Conference, (2007) 2559-2563.

DOI: 10.1109/wcnc.2007.27

Google Scholar

[8] M. Haddad, M. Debbah and A.M. Hayar. Distributed Power Allocation for Cognitive Radio. 9th International Symposium on Signal Processing and Its Applications, (2007) 1-4.

DOI: 10.1109/isspa.2007.4555401

Google Scholar

[9] I. Sooyeol, H. Jeon and L. Hyuckjae. Autonomous Distributed Power Control For Cognitive Radio Networks. Vehicular Technology Conference, (2008) 1-5.

Google Scholar

[10] O. Durowoju, K. Arshad and K. Moessner. Distributed Power Control for Cognitive Radios with Primary Protection via Spectrum Sensing. Vehicular Technology Conference, (2010) 1-5.

DOI: 10.1109/vetecf.2010.5594306

Google Scholar

[11] International Telecommunication Union. Propagation Data and Prediction Methods Required for the Design of Earth-Space Telecommunication Systems. Recommendation P. 618, ITU-R Recommendation, (2003).

Google Scholar

[12] R.D. Yates.A Framework for Uplink Power Control in Cellular Radio Systems. IEEE Journal of Selected Areas Communication, (1995)1341-1347.

DOI: 10.1109/49.414651

Google Scholar