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Stationary Equilibrium Strategies for Bandwidth Scanning. / Garnaev, A.; Trappe, W.

In: Lecture Notes in Computer Science, Vol. 8310, 2013, p. 168-183.

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Garnaev A, Trappe W. Stationary Equilibrium Strategies for Bandwidth Scanning. Lecture Notes in Computer Science. 2013;8310:168-183.

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Garnaev, A. ; Trappe, W. / Stationary Equilibrium Strategies for Bandwidth Scanning. In: Lecture Notes in Computer Science. 2013 ; Vol. 8310. pp. 168-183.

BibTeX

@article{7625ab6eab354b43b23c6e0b4484b8f7,
title = "Stationary Equilibrium Strategies for Bandwidth Scanning",
abstract = "In this paper we investigate the problem of designing a spectrum multi-step scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem, we model it as a two stage game, along with specifying an algorithm of scanning the spectrum and evaluating the stationary bandwidth of spectrum to scan. The game is solved explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the Invader's intention for illegal activity, which can lead even to multi-equilibrium situation. To select a proper equilibrium strategy the best response strategy algorithm can be applied which in the multi-equilibria case always converges for a finite number of iteration, meanwhile for mono-equilibria situation it does not converge, circling around the equilibrium. Also, we have shown that the detection probability and payoffs in some situation can",
author = "A. Garnaev and W. Trappe",
year = "2013",
language = "English",
volume = "8310",
pages = "168--183",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - Stationary Equilibrium Strategies for Bandwidth Scanning

AU - Garnaev, A.

AU - Trappe, W.

PY - 2013

Y1 - 2013

N2 - In this paper we investigate the problem of designing a spectrum multi-step scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem, we model it as a two stage game, along with specifying an algorithm of scanning the spectrum and evaluating the stationary bandwidth of spectrum to scan. The game is solved explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the Invader's intention for illegal activity, which can lead even to multi-equilibrium situation. To select a proper equilibrium strategy the best response strategy algorithm can be applied which in the multi-equilibria case always converges for a finite number of iteration, meanwhile for mono-equilibria situation it does not converge, circling around the equilibrium. Also, we have shown that the detection probability and payoffs in some situation can

AB - In this paper we investigate the problem of designing a spectrum multi-step scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem, we model it as a two stage game, along with specifying an algorithm of scanning the spectrum and evaluating the stationary bandwidth of spectrum to scan. The game is solved explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the Invader's intention for illegal activity, which can lead even to multi-equilibrium situation. To select a proper equilibrium strategy the best response strategy algorithm can be applied which in the multi-equilibria case always converges for a finite number of iteration, meanwhile for mono-equilibria situation it does not converge, circling around the equilibrium. Also, we have shown that the detection probability and payoffs in some situation can

M3 - Article

VL - 8310

SP - 168

EP - 183

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -

ID: 5773495