Anti-jamming communication in cognitive radio networks with unknown channel statistics

Recently, many opportunistic spectrum sensing and access protocols have been proposed for cognitive radio networks (CRNs). For achieving optimized spectrum usage, existing solutions model the spectrum sensing and access problem as a partially observed Markov decision process (POMDP) and assume that the information states and/or the primary users' (PUs) traffic statistics are known a priori to the secondary users (SUs). While theoretically sound, these existing approaches may not be effective in practice due to two main concerns. First, the assumptions they made are not practical, as before the communication starts, PUs' traffic statistics may not be readily available to the SUs. Secondly and more seriously, existing approaches are extremely vulnerable to malicious jamming attacks. A cognitive attacker can always jam the channels to be accessed by leveraging the same statistic information and stochastic dynamic decision making process that the SUs would follow. To address the above concerns, we formulate the problem of anti-jamming multichannel access in CRNs and solve it as a non-stochastic multi-armed bandit (NS-MAB) problem, where the secondary sender and receiver adaptively choose their arms (i.e., sending and receiving channels) to operate. The proposed protocol enables them to hop to the same set of channels with high probability in the presence of jamming. We analytically show the convergence of the learning algorithms, i.e., the performance difference between the secondary sende and receiver's optimal strategies is no more than O(20k/√ε √Tn ln n). Extensive simulations are conducted to validate the theoretical analysis and show that the proposed protocol is highly resilient to various jamming attacks.

[1]  P. Whittle Restless bandits: activity allocation in a changing world , 1988, Journal of Applied Probability.

[2]  Nicolò Cesa-Bianchi,et al.  Gambling in a rigged casino: The adversarial multi-armed bandit problem , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[3]  A. Viterbi CDMA: Principles of Spread Spectrum Communication , 1995 .

[4]  Peter Auer,et al.  The Nonstochastic Multiarmed Bandit Problem , 2002, SIAM J. Comput..

[5]  Baruch Awerbuch,et al.  Adaptive routing with end-to-end feedback: distributed learning and geometric approaches , 2004, STOC '04.

[6]  Magyar Tud The On-Line Shortest Path Problem Under Partial Monitoring , 2007 .

[7]  Ananthram Swami,et al.  Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework , 2007, IEEE Journal on Selected Areas in Communications.

[8]  Optimality of Myopic Sensing in Multi-Channel Opportunistic Access , 2008, 2008 IEEE International Conference on Communications.

[9]  Srdjan Capkun,et al.  Jamming-resistant Key Establishment using Uncoordinated Frequency Hopping , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[10]  Qing Zhao,et al.  A Restless Bandit Formulation of Multi-channel Opportunistic Access: Indexablity and Index Policy , 2008, ArXiv.

[11]  Srdjan Capkun,et al.  Detection of Reactive Jamming in Sensor Networks , 2009 .

[12]  Radha Poovendran,et al.  A coding-theoretic approach for efficient message verification over insecure channels , 2009, WiSec '09.

[13]  Srdjan Capkun,et al.  Efficient uncoordinated FHSS anti-jamming communication , 2009, MobiHoc '09.

[14]  Mingyan Liu,et al.  Optimality of Myopic Sensing in Multi-Channel Opportunistic Access , 2008, 2008 IEEE International Conference on Communications.

[15]  Peng Ning,et al.  Randomized Differential DSSS: Jamming-Resistant Wireless Broadcast Communication , 2010, 2010 Proceedings IEEE INFOCOM.

[16]  Zhu Han,et al.  Dogfight in Spectrum: Combating Primary User Emulation Attacks in Cognitive Radio Systems, Part I: Known Channel Statistics , 2010, IEEE Transactions on Wireless Communications.

[17]  Keith D. Kastella,et al.  Foundations and Applications of Sensor Management , 2010 .

[18]  Bhaskar Krishnamachari,et al.  Dynamic Multichannel Access With Imperfect Channel State Detection , 2010, IEEE Transactions on Signal Processing.

[19]  Venugopal V. Veeravalli,et al.  Algorithms for Dynamic Spectrum Access With Learning for Cognitive Radio , 2008, IEEE Transactions on Signal Processing.

[20]  Qing Zhao,et al.  Indexability of Restless Bandit Problems and Optimality of Whittle Index for Dynamic Multichannel Access , 2008, IEEE Transactions on Information Theory.

[21]  Peng Ning,et al.  USD-FH: Jamming-resistant wireless communication using Frequency Hopping with Uncoordinated Seed Disclosure , 2010, The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010).

[22]  K. J. Ray Liu,et al.  An anti-jamming stochastic game for cognitive radio networks , 2011, IEEE Journal on Selected Areas in Communications.

[23]  Zhu Han,et al.  Dogfight in Spectrum: Combating Primary User Emulation Attacks in Cognitive Radio Systems—Part II: Unknown Channel Statistics , 2010, IEEE Transactions on Wireless Communications.