Abstract
In cognitive radio networks (CRNs), spectrum prediction for inferring spectrum availability can help unlicensed users to discover spectrum holes earlier and to improve spectrum utilization more efficiently. Multilayer perceptron (MLP) neural network-based spectrum prediction model can identify the traffic characteristics of the spectrum only using the history data of the spectrum status. We investigate the statistic characteristics of the MLP neural network’s outputs, propose the gray decision to improve the performance of the MLP-base spectrum predictor. We prove that the performance of MLP-base predictor with gray decision will be improved significantly when the spectrum status change frequently.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Akyildiz, I.F., Lee, W.Y., Vuran, M.C., Mohanty, S.: A survey on spectrum management in cognitive radio networks. IEEE Commun. Mag. 46, 40–48 (2008)
Xing, X., Jing, T., Cheng, W., Huo, Y., Cheng, X.: Spectrum prediction in cognitive radio networks. IEEE Wirel. Commun. 20, 90–96 (2013)
Yarkan, S., Arslan, H.: Binary time series approach to spectrum prediction for cognitive radio. In: IEEE 66th Vehicular Technology Conference, pp. 1563–1567 (2007)
Akbar, I.A., Tranter, W.H.: Dynamic spectrum allocation in cognitive radio using hidden Markov models: poisson distributed case. In: IEEE SoutheastCon, pp. 196–201 (2007)
Chen, Z., Guo, N., Hu, Z., Qiu, R.C.: Channel state prediction in cognitive radio, part II: single-user prediction. In: Proceedings of IEEE Southeastcon, pp. 50–54 (2011)
Tumuluru, V.K., Wang, P., Niyato, D.: A neural network based spectrum prediction scheme for cognitive radio. In: IEEE International Conference on Communications, pp. 1–5 (2010)
Tumuluru, V.K., Wang, P., Niyato, D.: Channel status prediction for cognitive radio networks. Wirel. Commun. Mob. Comput. 12, 862–874 (2012)
Xing, X., Jing, T., Huo, Y., Li, H., Cheng, X.: Channel quality prediction based on Bayesian inference in cognitive radio networks. In: Proceedings IEEE INFOCOM, pp. 1465–1473 (2013)
Haykin, S.: Neural Networks and Learning Machines, 3rd edn., pp. 123–186. China Machine Press
Acknowledgment
This work was supported by the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province under Grant No. BK20160034, the National Natural Science Foundation of China under Grant No. 61401508 and No. 61671473, and in part by the Open Research Foundation of Science and Technology on Communication Networks Laboratory.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ge, J., Xu, Y., Liu, D., Kong, L., Chen, X. (2019). A Multilayer Perceptron Neural Network-Based Spectrum Prediction Approach with Gray Decision. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_292
Download citation
DOI: https://doi.org/10.1007/978-981-10-6571-2_292
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-6570-5
Online ISBN: 978-981-10-6571-2
eBook Packages: EngineeringEngineering (R0)