Location-aware cooperative spectrum sensing via Gaussian processes

2012 Australian Communications Theory Workshop, AusCTW'12

Volumn , Issue , 2012, Pages 19-24

  Nevat, Ido ^a   Peters, Gareth W ^b   Collings, Iain B ^a  

^a CSIRO   (Australia)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY DECISION; COGNITIVE RADIO NETWORK; COMPUTATIONALLY EFFICIENT; COOPERATIVE SPECTRUM SENSING; FUNCTION SPACES; GAUSSIAN PROCESSES; INTERFERENCE TEMPERATURE; LOCATION-AWARE; NUMERICAL RESULTS; PROBABILISTIC FRAMEWORK; REAL-WORLD APPLICATION; SEMIPARAMETRIC; SPATIAL LOCATION; SPATIAL SPECTRA; SPECTRAL HOLE; SPECTRUM ACCESS;

ALGORITHMS; COGNITIVE RADIO; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC);

COOPERATIVE COMMUNICATION;

EID: 84859097093     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AusCTW.2012.6164900     Document Type: Conference Paper

References (12)

1. J. Mitola III and G. Maguire Jr, "Cognitive radio: making software radios more personal," Personal Communications, IEEE, vol. 6, no. 4, pp. 13-18, 1999.
2. "IEEE P802.22/D0.5, Draft Standard for Wireless Regional Area Networks Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Policies and procedures for operation in the TV Bands," 2008.
3. J. Bazerque and G. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity," Signal Processing, IEEE Transactions on, vol. 58, no. 3, pp. 1847-1862, 2010.
4. A. Min, X. Zhang, and K. Shin, "Detection of small-scale primary users in cognitive radio networks," Selected Areas in Communications, IEEE Journal on, vol. 29, no. 2, pp. 349-361, 2011.
5. C. Rasmussen, "Gaussian processes in machine learning," Advanced Lectures on Machine Learning, pp. 63-71, 2004.
6. M. Haenggi, J. Andrews, F. Baccelli, O. Dousse, and M. Franceschetti, "Stochastic geometry and random graphs for the analysis and design of wireless networks," Selected Areas in Communications, IEEE Journal on, vol. 27, no. 7, pp. 1029-1046, 2009.
7. A. Molisch, D. Cassioli, C. Chong, S. Emami, A. Fort, B. Kannan, J. Karedal, J. Kunisch, H. Schantz, K. Siwiak et al., "A comprehensive standardized model for ultrawideband propagation channels," Antennas and Propagation, IEEE Transactions on, vol. 54, no. 11, pp. 3151-3166, 2006.
8. M. Lázaro-Gredilla, J. Quiñonero-Candela, C. Rasmussen, and A. Figueiras-Vidal, "Sparse spectrum gaussian process regression," The Journal of Machine Learning Research, vol. 11, pp. 1865-1881, 2010.
9. C. Rasmussen and C. Williams, Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). The MIT Press, 2005.
10. J. Besag, J. York, and A. Mollié, "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, vol. 43, no. 1, pp. 1-20, 1991.
11. S. Kirkpatrick, C. Gelatt, and M. Vecchi, "Optimization by simulated annealing," science, vol. 220, no. 4598, p. 671, 1983.
12. S. Shellhammer et al., "Performance of power detector sensors of dtv signals in ieee 802.22 wrans," in Proceedings of the first international workshop on Technology and policy for accessing spectrum. ACM, 2006, pp. 4-es.