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Optimization Letters

, Volume 6, Issue 7, pp 1499–1511 | Cite as

Capacity optimization through sensing threshold adaptation for cognitive radio networks

  • Fotis T. Foukalas
  • George T. Karetsos
  • Lazaros F. Merakos
Original Paper

Abstract

We propose capacity optimization through sensing threshold adaptation for sensing-based cognitive radio networks. The objective function of the proposed optimization is the maximization of the capacity at the secondary user subject to transmit power and sensing threshold constraints for protecting the primary user. After proving the concavity of capacity on sensing threshold, the problem is solved using the Lagrange duality decomposition method in conjunction with a subgradient iterative algorithm. The numerical results show that the proposed optimization can lead to significant capacity maximization for the secondary user as long as this is affordable to the primary user.

Keywords

Capacity optimization Cognitive radio network Convex optimization Lagrange duality Subgradient method 

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References

  1. 1.
    Haykin S.: Cognitive radio: Brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)CrossRefGoogle Scholar
  2. 2.
    Zhao Q., Sadler B.: A survey of dynamic spectrum access. IEEE Signal Process. Mag. 24(3), 79–89 (2007)CrossRefGoogle Scholar
  3. 3.
    Kang X., Liang Y.-C., Garg H.K., Zhang L.: Sensing-based spectrum sharing in cognitive radio networks. IEEE Trans. Veh. Tech. 58(8), 4649–4654 (2009)CrossRefGoogle Scholar
  4. 4.
    Musavian L., Aïssa S.: Capacity and power allocation for spectrum-sharing communications in fading channels. IEEE Trans Wirel. Commun. 8(1), 148–156 (2009)CrossRefGoogle Scholar
  5. 5.
    Xin K., Liang Y.-C., Nallanathan A., Garg H.K., Zhang R.: Optimal power allocation for fading channels in cognitive radio networks: ergodic capacity and outage capacity. IEEE Trans. Wirel. Commun. 8(2), 940–950 (2009)CrossRefGoogle Scholar
  6. 6.
    Oliveira, C., Pardalos, P.M.: A distributed optimization algorithm for power control in wireless ad hoc networks. In: IEEE 18th International Parallel and Distributed Processing Symposium (IPDPS’04), vol. 7, pp. 177–185. Santa Fe, New Mexico (2004)Google Scholar
  7. 7.
    Choi, H., Jang, K., Cheong, Y.: Adaptive sensing threshold control based on transmission power in cognitive radio systems. In: 3rd International Conference on Cognitive Radio or Wireless Networks and Communication, CrownCom (2008)Google Scholar
  8. 8.
    Digham F.F., Alouni M.-S., Simon M.K.: On the energy detection of unknown signals over fading channels. IEEE Trans. Commun. 55(1), 21–24 (2007)CrossRefGoogle Scholar
  9. 9.
    Zhang, R.: Optimal power control over fading cognitive radio channels by exploiting primary user CSI. In: Proceedings of the IEEE Global Communication Conference (Globecom), New Orleans, USA (2008)Google Scholar
  10. 10.
    Chen Y., Zhao Q., Swami A.: Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors. IEEE Trans. Inf. Theory 54(5), 2053–2071 (2008)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Stephen, B., Lieven, V.: Convex optimization. Cambridge University Press, London (2004). ISBN: 978-0-521-83378-3Google Scholar
  12. 12.
    Nedić, A.: Subgradient methods for convex minimization. Ph.D. dissertation, MIT (2002)Google Scholar
  13. 13.
    Andrea, G.: Wireless Communications. Campridge University Press, London (2005). ISBN: 978-0521837163Google Scholar
  14. 14.
    Resende, M.G.C., Pardalos, P.M.: Handbook of Optimization in Telecommunications. Springer, New York (2006). ISBN: 9780387306629 (978-0387306629)Google Scholar
  15. 15.
    Bertsekas, D.P.: Nonlinear programming, 2nd edn. Athena Scientific, Belmont (1995). ISBN: 1886529000 (1-886529-00-0)Google Scholar
  16. 16.
    Pardalos, P.M., Resende, M.G.C.: Handbook of Applied Optimization. Oxford University Press, USA (2002). ISBN: 0195125940 (978-0195125948)Google Scholar
  17. 17.
    Ribeiro A., Giannakis G.B.: Separation principles in wireless networking. IEEE Trans. Inf. Theory. 56(9), 4488–4505 (2010)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Palomar D.P., Chiang M.: A tutorial on decomposition methods for network utility maximization. IEEE J. Sel. Areas Commun. 24(8), 1439–1451 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Fotis T. Foukalas
    • 1
  • George T. Karetsos
    • 2
  • Lazaros F. Merakos
    • 1
  1. 1.Department of Informatics and TelecommunicationsNational Kapodistrian University of AthensAthensGreece
  2. 2.Department of Information Technology and TelecommunicationsTEI of LarissaLarissaGreece

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