Abstract
Cognitive radio networking (CRN) is a promising technology to improve the spectrum utilization by allowing secondary users (unlicensed users) to opportunistically access white space (spectrum holes) in licensed bands. Monitoring the detailed characteristics of an operational cognitive radio network is critical to many system administrative tasks. However, very limited work has been done in this area. In this paper, we study the passive secondary user monitoring problem in an unslotted cognitive radio network, where the users’ traffic statistics are unknown in priori. We formulate the problem as a multi-armed bandit (MAB) problem with weighted virtual reward. We propose a dynamic sniffer-channel assignment policy to capture as much as interested user data. Simulation results show that the proposed policy can achieve a logarithmic regret with relative scalability.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
FCC: Unlicensed operations in the tv broadcast bands, second memorandum opinion and order. FCC 10-174 (September 2010)
Haykin, S.: Cognitive radio: Brain-empowered wireless communications. IEEE JSAC 23(2), 201–220 (2005)
Akyildiz, I.F., Lee, W., Vuran, M.C., Mohanty, S.: Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks 50(13), 2127–2159 (2006)
Wang, J., Ghosh, M., Challapali, K.: Emerging cognitive radio applications: A survey. IEEE Communications Magazine 49(3), 74–81 (2011)
Chen, S., Zeng, K., Mohapatra, P.: Efficient data capturing for network forensics in cognitive radio networks. In: 2011 19th IEEE International Conference on Network Protocols (ICNP), pp. 176–185. IEEE (2011)
Yeo, J., Youssef, M., Agrawala, A.: A framework for wireless lan monitoring and its applications. In: Proceedings of the 3rd ACM Workshop on Wireless Security, pp. 70–79. ACM (2004)
Chhetri, A., Nguyen, H., Scalosub, G., Zheng, R.: On quality of monitoring for multi-channel wireless infrastructure networks. In: Proceedings of the Eleventh ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 111–120. ACM (2010)
Arora, P., Szepesvari, C., Zheng, R.: Sequential learning for optimal monitoring of multi-channel wireless networks. In: INFOCOM, 2011 Proceedings IEEE, pp. 1152–1160. IEEE (2011)
Robbins, H.: Some aspects of the sequential design of experiments. Bulletin of the American Mathematical Society 58(5), 527–535 (1952)
Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Machine Learning 47(2), 235–256 (2002)
Lai, L., El Gamal, H., Jiang, H., Poor, H.: Cognitive medium access: Exploration, exploitation, and competition. IEEE Transactions on Mobile Computing 10(2), 239–253 (2011)
Liu, K., Zhao, Q., Krishnamachari, B.: Decentralized multi-armed bandit with imperfect observations. In: 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 1669–1674. IEEE (2010)
Liu, K., Zhao, Q.: Distributed learning in multi-armed bandit with multiple players. IEEE Transactions on Signal Processing 58(11), 5667–5681 (2010)
Tehrani, P., Zhao, Q., Tong, L.: Multi-channel opportunistic spectrum access in unslotted primary systems with unknown models. In: 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 157–160. IEEE (2011)
Zhao, Q., Sadler, B.: A survey of dynamic spectrum access. IEEE Signal Processing Magazine 24(3), 79–89 (2007)
Chen, S., Tong, L.: Low-complexity distributed spectrum sharing among multiple cognitive users. In: Military Communications Conference, 2010-MILCOM 2010, pp. 2274–2279. IEEE (2010)
Lai, T., Robbins, H.: Asymptotically efficient adaptive allocation rules. Advances in Applied Mathematics 6(1), 4–22 (1985)
Agrawal, R.: Sample mean based index policies with o (log n) regret for the multi-armed bandit problem. Advances in Applied Probability, 1054–1078 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yi, S., Zeng, K., Xu, J. (2012). Secondary User Monitoring in Unslotted Cognitive Radio Networks with Unknown Models. In: Wang, X., Zheng, R., Jing, T., Xing, K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2012. Lecture Notes in Computer Science, vol 7405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31869-6_56
Download citation
DOI: https://doi.org/10.1007/978-3-642-31869-6_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31868-9
Online ISBN: 978-3-642-31869-6
eBook Packages: Computer ScienceComputer Science (R0)