1 |
J.W. Wang, R. Adriman, "Analysis of opportunistic spectrum access in cognitive radio networks using hidden Markov model with state prediction," EURASIP Journal on Wireless Communications and Networks, vol.2015, no.10, pp.1-8, 2015.
|
2 |
K.S. Narendra, K. Parthasarathy, "Identification and control of dynamical systems using neural networks," IEEE Transaction on Neural Networks, vol.1, no.1, pp. 4-27, 1990.
DOI
|
3 |
D. Svozil, V. Kvasnicka, J. Pospichal, "Introduction to multi-layer feed-forward neural networks," Chemometrics and Intelligent Laboratory Systems, vol.39, no.1, pp.43-63, 1997.
DOI
|
4 |
S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice Hall, New Jersey, USA, pp.161-175, 1999.
|
5 |
M. Wellens, J. Riihijarvi, P.Mahonen, "Empirical time and frequency domain models of spectrum use," Phyical. Communication, vol.2, no.1-2, pp.10-32, 2009.
DOI
|
6 |
M. Wellens, P. Mahonen, "Lessons learned from an extensive spectrum occupancy measurement campaign and a stochastic duty cycle model," Mobile Networks and Applications, vol.15, no.3, pp.461-474, 2010.
DOI
|
7 |
J. G. De Gooijer, R. J. Hyndman, "25 years of Time Series Forecasting," International Journal of Forecasting, vol.22, no.3, pp.443-473, 2006.
DOI
|
8 |
M. Hermans, B. Schrauwen, "Training and analyzing deep recurrent neural networks," in Proc. of Advances in Neural Information Processing Systems 26, Lake Tahoe, pp. 190-198, 5-10 December, 2013.
|
9 |
V. Nair, G.E. Hinton, "Rectified Linear Units Improve Restricted Boltzmann Machines," in Proc. of International Conference on Machine Learning, Haifa, Israel, 21-24 June 2010.
|
10 |
S. B. Taieb, G. Bontempi, A. F. Atiya, "Sorjamaa, A. A review and comparison of strategies for multi-step ahead time series forecasting based on the {NN5} forecasting competition," Expert Syst. Appl., vol.39, no. 8, pp. 7067-7083, 2012.
DOI
|
11 |
Z. Chen, N. Guo, Z. Hu, R. Qiu, "Experiment validation of channel state prediction considering delays in practical cognitive radio," IEEE Transactions on Vehicular Technology, vol.60, no.4, pp. 1314-1325, 2011.
DOI
|
12 |
C. Hamzacebi, D. Akay, F. Kutay, "Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting," Expert Syst. Appl., vol.36, no.2, pp.3839-3844, 2009.
DOI
|
13 |
A. Sorjamaa, J. Hao, N. Reyhani, Y. Ji, A. Lendasse, "Methodology for long-term prediction of time series," Neurocomputing, vol.70, no.16-18, pp.2861-2869, 2007.
DOI
|
14 |
A. Sahai, N. Hoven, R. Tandra, "Some fundamental limits on cognitive radio," in Proc. of the Allerton Conference on Communication, Control, and Computing, Monticello, UT, USA, 29 Sep.-1 October, 2004.
|
15 |
M. Ghozzi, F. Marx, M. Dohler, J. Palicot, "Cyclostatilonarilty-based test for detection of vacant frequency bands," in Proc. of the 2nd International Conference on Cognitive Radio Oriented Wireless Network and Communication, Mykonos Island, Greek, 8-10 June, 2006.
|
16 |
P.D. Sutton, K.E. Nolan, L.E. Doyle, "Cyclostationary signature in practical cognitive radio applications," IEEE JSAC, vol.26, no.1, pp.13-24, 2008.
|
17 |
L. Melian-Gutierrez, S. Zazo, J.L. Blanco-Murillo, "Efficiency improvement of HF communications using cognitive radio principles," in Proc. of Ionospheric Radio Systems and Techniques Conference, York, UK, 15-17 May 2012.
|
18 |
B. Nicola, R.T. Bheemarjuna, B.S. Manoj, "A Neural Network based Cognitive Controller for Dynamic Channel Selection," in Proc. of IEEE International Conference on Communications, Dresden, Germany, 14-18 June, 2009
|
19 |
Z. Chen, N. Guo, Z. Hu, R. Qiu, "Channel state prediction in cognitive radio, part ii: Single-user prediction," in Proc. of IEEE Southeastcon, Nashville, USA 17-20 March, 2011.
|
20 |
S. H. Shon, S. J. Jang, Kim J. M, "HMM-based adaptive frequency hopping cognitive radio system to reduce interference time and to improve throughput," KSII transaction on internet. and information system, pp.475-490, 2010.
|
21 |
G.C. Tiao, R. S. Tsay, "Some advances in nonlinear and adaptive modeling in Time Series," Journal of Forecasting, vol.13, no.2, pp. 109-131, 1994.
DOI
|
22 |
V. Tumuluru, P. Wang, D. Niyato, "Channel status prediction for cognitive radio networks," Wireless Communications & Mobile Computing, vol.12, no.10, pp. 862-874, 2012.
DOI
|
23 |
J. Mitola III, "Cognitive radio for flexible mobile multimedia communications," Journal Mobile Networks and Applications, vol.6, no.5, pp. 435-441, 2001.
DOI
|
24 |
S. Haykin, "Cognitive radio: Brain-empowered wireless communications," IEEE JSAC, vol.23, no.2, pp.201-220, 2005.
|
25 |
S. Haykin, Cognitive Dynamic Systems: Perception-Action Cycle, Radar and Radio, Cambridge University Press, London, pp.14-15, 2012.
|
26 |
P. Huang, C.J. Liu, L. Xiao, J. Chen, "Wireless Spectrum Occupancy Prediction Based on Partial Periodic Pattern Mining," IEEE Transactions on Parallel & Distributed System, vol.25, no.7, pp.1925-1934, 2014.
DOI
|
27 |
F.R. Huang,W. Wang, H.Y. Luo, G.D. Yu, Z.Y. Zhang, "Prediction-Based Spectrum Aggregation with Hardware Limitation in Cognitive Radio Networks," in Proc. of IEEE 71st Vehicular Technology Conference, Taipei, Taiwan, 16-19 May, 2010.
|
28 |
V. Tumuluru, P. Wang, D. Niyato, "A neural network based spectrum prediction scheme for cognitive radio," in Proc. of IEEE International Conference on Communications, Cape Town, South Africa, 23-27 May, 2010.
|