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dc.contributor.authorAziz, Farhan
dc.contributor.authorShamma, Jeff S.
dc.contributor.authorStuber, Gordon L.
dc.date.accessioned2017-03-07T13:47:40Z
dc.date.available2017-03-07T13:47:40Z
dc.date.issued2017-02-22
dc.identifier.citationAziz F, Shamma J, Stuber GL (2017) Jammer Type Estimation in LTE with a Smart Jammer Repeated Game. IEEE Transactions on Vehicular Technology: 1–1. Available: http://dx.doi.org/10.1109/tvt.2017.2672682.
dc.identifier.issn0018-9545
dc.identifier.issn1939-9359
dc.identifier.doi10.1109/tvt.2017.2672682
dc.identifier.urihttp://hdl.handle.net/10754/622981
dc.description.abstractLTE/LTE-Advanced networks are known to be vulnerable to denial-of-service (DOS) and loss-of-service attacks from smart jammers. The interaction between the network and the smart jammer has been modeled as an infinite-horizon general-sum (non-zero-sum) Bayesian game with asymmetric information, with the network being the uninformed player. Although significant work has been done on optimal strategy computation and control of information revelation of the informed player in repeated asymmetric information games, it has been limited to zero-sum games with perfect monitoring. Recent progress on the strategy computation of the uninformed player is also limited to zero-sum games with perfect monitoring and is focused on expected payoff formulations. Since the proposed formulation is a general-sum game with imperfect monitoring, existing formulations cannot be leveraged for estimating true state of nature (the jammer type). Hence, a threat-based mechanism is proposed for the uninformed player (the network) to estimate the informed player’s type (jammer type). The proposed mechanism helps the network resolve uncertainty about the state of nature (jammer type) so that it can compute a repeated-game strategy conditioned on its estimate. The proposed algorithm does not rely on the commonly assumed “full monitoring” premise, and uses a combination of threat-based mechanism and non-parametric estimation to estimate the jammer type. In addition, it does not require any explicit feedback from the network users nor does it rely on a specific distribution (e.g., Gaussian) of test statistic. It is shown that the proposed algorithm’s estimation performance is quite robust under realistic modeling and observational constraints despite all the aforementioned challenges.
dc.description.sponsorshipThe research reported in this publication was supported in part by funding from the US AFOSR/MURI project # FA9550-10-1-0573, the US ARO project # W911NF-09-1-0553, and the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/7862285/
dc.rights(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.subjectnonparametric estimation
dc.subjectLTE/LTE-A
dc.subjectsmart jamming
dc.subjectBayesian games with asymmetric information
dc.subjectthreat-based mechanism
dc.titleJammer Type Estimation in LTE with a Smart Jammer Repeated Game
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalIEEE Transactions on Vehicular Technology
dc.eprint.versionPost-print
dc.contributor.institutionWireless Systems Laboratory (WSL), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
kaust.personShamma, Jeff S.
refterms.dateFOA2018-06-13T18:13:01Z
dc.date.published-online2017-02-22
dc.date.published-print2017-08


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