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Communication Scheduling and Remote Estimation With Adversarial Intervention 预览

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摘要 We study a communication scheduling and remote estimation problem within a worst-case scenario that involves a strategic adversary. Specially, a remote sensing system consisting of a sensor, an encoder and a decoder is configured to observe,transmit, and recover a discrete time stochastic process. At each time step, the sensor makes an observation on the state variable of the stochastic process. The sensor is constrained by the number of transmissions over the time horizon, and thus it needs to decide whether to transmit its observation or not after making each measurement. If the sensor decides to transmit,it sends the observation to the encoder, who then encodes and transmits the observation to the decoder. Otherwise, the sensor and the encoder maintain silence. The decoder is required to generate a real-time estimate on the state variable. The sensor,the encoder, and the decoder collaborate to minimize the sum of the communication cost for the sensor, the encoding cost for the encoder, and the estimation error for the decoder. There is also a jammer interfering with the communication between the encoder and the decoder, by injecting an additive channel noise to the communication channel. The jammer is charged for the jamming power and is rewarded for the estimation error generated by the decoder, and it aims to minimize its net cost. We consider a feedback Stackelberg game with the sensor, the encoder, and the decoder as the composite leader, and the jammer as the follower. Under some technical assumptions, we obtain a feedback Stackelberg solution, which is threshold based for the scheduler,and piecewise affine for the encoder and the decoder. We also generate numerical results to demonstrate the performance of the remote sensing system under the feedback Stackelberg solution.
出处 《自动化学报:英文版》 CSCD 2019年第1期32-44,共13页 IEEE/CAA Journal of Automatica Sinica
基金 the U.S.Army Research Labs(ARL)under IoBT(479432-239012-191100) in part by the U.S. Army Research Office(ARO)(W911NF-16-1-0485) in part by the Office of Naval Research(ONR)MURI(N00014-16-1-2710).
作者简介 Xiaobin Gao received his B.S. degree in electricalengineering from the University of Michigan, Ann-Arbor, in 2012, and another B.S. degree in mechanicalengineering from Shanghai Jiao Tong Universityin the same year;Emrah Akyol is an Assistant Professor of Electricaland Computer Engineering at the State Universityof New York at Binghamton. He received his Ph.D.degree in 2011 from the University of California atSanta Barbara;Corresponding author:Tamer Basar.(S’71?M’73?SM’79?F’83?LF’13)is with the University of Illinois at Urbana-Champaign, where he holds the academic positionsof Swanlund Endowed Chair;Center for AdvancedStudy Professor of Electrical and Computer Engineering;Research Professor at the CoordinatedScience Laboratory;and Research Professor at theInformation Trust Institute.
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