Open Access
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
Article Number 05010
Number of page(s) 6
Section Modern Communication Technology and Applications
Published online 26 April 2016
  1. C. Kim, C. Leem, S. Kang, “Policy and technology of dynamic spectrum access in Korea,” 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, pp. 1–4, 2008, doi: 10.1109/CROWNCOM.2008.4562456.
  2. M. Mchenry, E. Livsics, T. Nguyen, “XG dynamic spectrum access field test results,” IEEE Communication Magazine, pp. 51–57,Jun. 2007. [CrossRef]
  3. J. Revathy, M. Senthil, “Resource allocation in next generation networks using game theory,” 2014 International Conference on Information Communication and Embedded Systems (ICICES), pp. 1–4.
  4. Z. Wu, P. Cheng, X. Wang, “Cooperative spectrum allocation for cognitive radio network: an evolutionary approach,” 2011 IEEE International Conference on Communications (ICC), pp. 1–5.
  5. Y. Li, L. Zhao, C. Wang, “Aggregation-based spectrum allocation algorithm in cognitive radio networks,” Network Operations and Management Symposium (NOMS), IEEE, pp. 506–509.
  6. A. Plummer, S. Biswas, “Distributed spectrum assignment for cognitive networks with heterogeneous spectrum opportunities,” Wireless Communications and Mobile Computing, pp. 1239–1253, Sep. 2011. [CrossRef]
  7. F. Wu, Y. Mao, S. Leng, “A carrier aggregation based resource allocation scheme for pervasive wireless networks,” 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC), IEEE, pp. 196–201.
  8. C. Li, W. Liu, Q. Liu, “Spectrum aggregation based spectrum allocation for cognitive radio networks,” Wireless Communications and Networking Conference (WCNC), IEEE, pp. 1626–1631.
  9. Y. Song, C. Zhang, Y. Fang, “Multiple multidimensional knapsack problem and its applications in cognitive radio networks,” Military Communications Conference, MILCOM. pp. 1–7.
  10. P. Setoodeh, S. Haykin, “Robust transmit power control for cognitive radio,” Proc. of the IEEE, vol. 97, no.5, pp. 915–939, May. 2009. [CrossRef]
  11. S. Sun, W. Ni, Y. Zhu, “Robust power control in cognitive radio networks: a distributed way,” 2011 IEEE International Conference on Communications (ICC), pp. 1–6.
  12. S. Parsaeefard, A. Sharafat, “Robust distributed power control in cognitive radio networks,” IEEE Transactions on Mobile Computing, pp. 609–620, Apr. 2013. [CrossRef]
  13. J. Misic, V. Misic, “Probability distribution of spectral hole duration in cognitive networks,” INFOCOM, 2014 Proc. IEEE. pp. 2103–2111.
  14. Y. Saleem, M. Rehmani, “Primary radio user activity models for cognitive radio networks: A survey,” Journal of Network and Computer Applications, pp. 1–16, Mar. 2014. [CrossRef]
  15. G. Casella, R. Berger, “Statistical inference. Pacific Grove,” CA: Duxbury, 2002.
  16. M. Abramowitz, S. Irene, “Handbook of mathematical functions: with formulas, graphs, and mathematical tables,” Courier Corporation, 1964.
  17. S. Martello, P. Toth, “Knapsack problems: algorithms and computer implementations,” John Wiley Sons, 1990.
  18. Y. Wang, K. Pedersen, T. Sorensen, “Utility Maximization in LTE-Advanced Systems with Carrier Aggregation,” 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), pp. 1–5.