Jamming Bandits - A Novel Learning Method for Optimal Jamming

IEEE Transactions on Wireless Communications

Volumn 15, Issue 4, 2016, Pages 2792-2808

  Amuru, SaiDhiraj ^a   Tekin, Cem ^b   Van Der Schaar, Mihaela ^c   Buehrer, R Michael ^a  

^a Virginia Polytechnic Institute and State University   (United States)

^b BILKENT UNIVERSITY   (Turkey)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

convergence; Jamming; learning; multiarmed bandits; optimal; regret

Indexed keywords

ALGORITHMS; ELECTRONIC WARFARE; JAMMING; NETWORK LAYERS; REINFORCEMENT LEARNING; TRANSMITTERS;

CONVERGENCE; LEARNING; MULTI ARMED BANDIT; OPTIMAL; REGRET;

LEARNING ALGORITHMS;

EID: 84963864066     PISSN: 15361276     EISSN: None     Source Type: Journal    
DOI: 10.1109/TWC.2015.2510643     Document Type: Conference Paper

References (43)

1. S. Amuru, C. Tekin, M. van der Schaar, and R. M. Buehrer, "A systematic learning method for optimal jamming," in Proc. Int. Conf. Commun. (ICC), Jun. 2015, pp. 2822-2827.
2. A. D. Wyner, "The wire-tap channel," Bell Syst. Tech. J., vol. 54, no. 8, pp. 1335-1387, Jan. 1975.
3. I. Csiszar and J. Korner, "Broadcast channels with confidential messages," IEEE Trans. Inf. Theory, vol. IT-24, no. 3, pp. 339-348, May 1978.
4. Y. Liang, H. V. Poor, and S. Shamai Shitz, "Information theoretic security," Found. Trends Commun. Inf. Theory, vol. 5, no. 7, pp. 355-580, 2008.
5. T. Basar, "The Gaussian test channel with an intelligent jammer," IEEE Trans. Inf. Theory, vol. IT-29, no. 1, pp. 152-157, Jan. 1983.
6. M. Medard, "Capacity of correlated jamming channels," in Proc. Allerton Conf. Commun. Control Comput., Monticello, IL, USA, 1997, pp. 1043-1052.
7. A. Kashyap, T. Basar, and R. Srikant, "Correlated jamming on MIMO Gaussian fading channels," IEEE Trans. Inf. Theory, vol. 50, no. 9, pp. 2119-2123, Sep. 2004.
8. A. Mukherjee and A. L. Swindlehurst, "Jamming games in the MIMO wiretap channel with an active eavesdropper," IEEE Trans. Signal Process., vol. 62, no. 1, pp. 82-91, Jan. 2013.
9. Y. O. Basciftci, C. E. Koksal, and F. Ozguner, "To obtain or not to obtain CSI in the presence of hybrid adversary," in Proc. IEEE Int. Symp. Inf. Theory, Istanbul, Turkey, Jan. 2013, pp. 2865-2869.
10. M. Azizoglu, "Convexity properties in binary detection problems," IEEE Trans. Inf. Theory, vol. 42, no. 4, pp. 1316-1321, Jul. 1996.
11. S. Bayram et al., "Optimum power allocation for average power constrained jammers in the presence of non-Gaussian noise," IEEE Commun. Lett., vol. 16, no. 8, pp. 1153-1156, Aug. 2012.
12. S. Amuru and R. M. Buehrer, "Optimal jamming strategies in digital communications-impact of modulation," in Proc. Global Commun. Conf., Austin, TX, USA, Dec. 2014, pp. 1619-1624.
13. S. Amuru and R. M. Buehrer, "Optimal jamming against digital modulation," IEEE Trans. Inf. Forensics Security, vol. 10, no. 10, pp. 2212-2224, Oct. 2015.
14. K. Dabcevic, A. Betancourt, L. Marcenaro, and C. S. Regazzoni, "A fictitious play-based game-theoretical approach to alleviating jamming attacks for cognitive radios," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP), Florence, Italy, May 2014, pp. 8158-8162.
15. Y. E. Sagduyu, R. A. Berry, and A. Ephremides, "Jamming games in wireless networks with incomplete information," IEEE Commun. Mag., vol. 49, no. 8, pp. 112-118, Aug. 2011.
16. R. McEliece and W. Stark, "An information theoretic study of communication in the presence of jamming," in Proc. Int. Conf. Commun., 1981, pp. 45.3.1-45.3.5.
17. S. Shamai Shitz and S. Verdú, "Worst-case power constrained noise for binary-input channels," IEEE Trans. Inf. Theory, vol. 38, no. 5, pp. 1494-1511, Sep. 1992.
18. H. I. Volos and R. M. Buehrer, "Cognitive engine design for link adaptation: An application to multi-antenna systems," IEEE Trans. Wireless Commun., vol. 9, no. 9, pp. 2902-2913, Sep. 2010.
19. H. I. Volos and R. M. Buehrer, "Cognitive radio engine training," IEEE Trans. Wireless Commun., vol. 11, no. 11, pp. 3878-3889, Nov. 2012.
20. B. Wang, Y. Wu, and K. J. R. Liu, "An anti-jamming stochastic game in cognitive radio networks," IEEE J. Sel. Areas Commun., vol. 29, no. 4, pp. 877-889, Apr. 2011.
21. Y. Wu, B. Wang, K. J. R. Liu, and T. C. Clancy, "Anti-jamming games in multi-channel cognitive radio networks," IEEE J. Sel. Areas Commun., vol. 30, no. 1, pp. 4-15, Jan. 2012.
22. Y. L. Gwon, S. Dastangoo, C. E. Fossa, and H. T. Kung, "Competing mobile network game: Embracing antijamming and jamming strategies with reinforcement learning," in Proc. Commun. Netw. Security, Washington, DC, USA, Oct. 2013, pp. 28-36.
23. C. Tekin and M. Liu, "Online learning in opportunistic spectrum access: A restless bandit approach," in Proc. Int. Conf. Comput. Commun., Shanghai, China, Apr. 2011, pp. 2462-2470.
24. S. Ahmad, M. Liu, T. Javidi, Q. Zhao, and B. Krishnamachari, "Optimality of myopic sensing in multichannel opportunistic access," IEEE Trans. Inf. Theory, vol. 55, no. 9, pp. 4040-4050, Sep. 2009.
25. Y. Gai, B. Krishnamachari, and R. Jain, "Learning multiuser channel allocations in cognitive radio networks: A combinatorial multi-armed bandit formulation," in Proc. New Front. Dyn. Spectr. (DYSPAN), Singapore, Apr. 2010, pp. 1-9.
26. Q. Wang, P. Xu, K. Ren, and X.-Y. Li, "Towards optimal adaptive UFH-based anti-jamming wireless communication," IEEE J. Sel. Areas Commun., vol. 30, no. 1, pp. 16-30, Jan. 2012.
27. N. Gulati and K. R. Dandekar, "Learning state selection for reconfigurable antennas: A multi-armed bandit approach," IEEE Trans. Antenna Propag., vol. 62, no. 3, pp. 1027-1038, Mar. 2014.
28. P. Auer, N. Cesa-Bianchi, and P. Fischer, "Finite-time analysis of the multi-armed bandit problem," Mach. Learn., vol. 47, no. 2, pp. 235-256, May 2002.
29. P. Auer, N. Cesa-Bianchi, Y. Freund, and R. E. Schapire, "The nonstochastic multi-armed bandit problem," SIAM J. Comput., vol. 32, no. 1, pp. 48-77, Jan. 2002.
30. R. Kleinberg, "Nearly tight bounds for the continuum-armed bandit problem," in Proc. Neural Inf. Proc. Syst., 2004, pp. 201-208.
31. R. Kleinberg et al.., "Multi-armed bandits in metric spaces," in Proc. Symp. Theory Comput. (STOC), 2008, pp. 681-690.
32. S. Magureanu et al., "Lipschtiz bandits: Regret lower bounds and optimal algorithms," in Proc. Conf. Learn. Theory (COLT), 2014, pp. 975-999.
33. S. Bubeck et al., "Online optimization in X-armed bandits," in Proc. Neural Inf. Proc. Syst. (NIPS), 2008, pp. 201-208.
34. A. Slivkins, "Contextual bandits with similarity information," in Proc. Conf. Learn. Theory (COLT), 2011, pp. 2533-2568.
35. 3GPP, "Evolved universal terrestrial radio access (E-UTRA); LTE physical layer-general description (Release 8)," TS 36.201, Nov. 2007.
36. S. Amuru and R. M. Buehrer, "Optimal jamming using delayed learning," in Proc. Mil. Commun. Conf., Baltimore, MD, USA, Oct. 2014. pp. 1528-1533.
37. Z. Serceki and M. Wilhoyte, "Method for determining packet error rate of wireless LAN stations," U.S. Patent 200 400 761 38A1, Apr. 22, 2004.
38. J.-Y. Audibert, R. Munos, and C. Szepesvari, "Exploration-exploitation trade-off using variance estimates in multi-armed bandits," Theor. Comput. Sci., vol. 410, no. 19, pp. 1876-1902, Apr. 2009.
39. S. Amuru, C. Tekin, M. van der Schaar, and R. M. Buehrer, "Jamming bandits," in arXiv preprint arXiv:1411.3652, Nov. 2014.
40. R. A. Poisel, Introduction to Communication Electronic Warfare Systems. Norwood, MA, USA: Artech House, 2008.
41. P. Auer and R. Ortner, "UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem," Period. Math. Hung., vol. 61, pp. 55-65, 2010.
42. M. Strasser, S. Čapkun, and M. Čagalj, "Jamming-resistant key establishment using uncoordinated frequency hopping," in Proc. IEEE Symp. Security Privacy, Oakland, CA, USA, May 2008, pp. 64-78.
43. C. Tekin, L. Canzian, and M. van der Schaar, "Context adaptive big data stream mining," in Proc. Allerton Conf. Commun. Control Comput., Monticello, IL, USA, Oct. 2014, pp. 483-490.