Sensor Selection and Design for Binary Hypothesis Testing in the Presence of a Cost Constraint

Oymak, Berkay; Dulek, Berkan; Gezici, Sinan

doi:10.1109/tsipn.2020.3016471

Cited by 3 publications

(2 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…r Swap Algorithm with Random Initialization: This algorithm is considered for comparison purposes similar to the local optimization algorithm in [42]. In this algorithm, we use the proposed swap algorithm (Algorithm 1) with arbitrarily generated initial selection vectors (inputs) for the eavesdropper selection problem or the jammer selection problem.…”

Section: Simulation Resultsmentioning

confidence: 99%

Eavesdropper and Jammer Selection in Wireless Source Localization Networks

Ozturk

Gezici

2021

IEEE Trans. Signal Process.

Self Cite

View full text Add to dashboard Cite

We consider a wireless source localization network in which a target node emits localization signals that are used by anchor nodes to estimate the target node position. In addition to target and anchor nodes, there can also exist eavesdropper nodes and jammer nodes which aim to estimate the position of the target node and to degrade the accuracy of localization, respectively. We first propose the problem of eavesdropper selection with the goal of optimally placing a given number of eavesdropper nodes to a subset of possible positions to estimate the target node position as accurately as possible. As the performance metric, the Cramér-Rao lower bound (CRLB) related to the estimation of the target node position by eavesdropper nodes is derived, and its convexity and monotonicity properties are investigated. By relaxing the integer constraints, the eavesdropper selection problem is approximated by a convex optimization problem and algorithms are proposed for eavesdropper selection. Then, the problem of jammer selection is proposed where the aim is to optimally place a given number of jammer nodes to a subset of possible positions for degrading the localization accuracy of the network as much as possible. A CRLB expression from the literature is used as the performance metric, and its concavity and monotonicity properties are derived. Also, a convex optimization problem is derived after relaxation. Finally, the joint eavesdropper and jammer selection problem is proposed with the goal of placing certain numbers of eavesdropper and jammer nodes to a subset of possible positions.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Eavesdropper and Jammer Selection in Wireless Source Localization Networks

Ozturk

Gezici

2021

IEEE Trans. Signal Process.

Self Cite

View full text Add to dashboard Cite

show abstract

“…• Swap Algorithm with Random Initialization: This algorithm is considered for comparison purposes similar to the local optimization algorithm in [42]. In this algorithm, we use the proposed swap algorithm (Algorithm 1) with arbitrarily generated initial selection vectors (inputs) for the eavesdropper selection problem or the jammer selection problem.…”

Section: Simulation Resultsmentioning

confidence: 99%

Eavesdropper Selection Strategies in Wireless Source Localization Networks

Ozturk

Gezici

2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

Self Cite

View full text Add to dashboard Cite

We consider a wireless source localization network in which a target node emits localization signals that are used by anchor nodes to estimate the target node position. In addition to target and anchor nodes, there can also exist eavesdropper nodes and jammer nodes which aim to estimate the position of the target node and to degrade the accuracy of localization, respectively. We first propose the problem of eavesdropper selection with the goal of optimally placing a given number of eavesdropper nodes to a subset of possible positions in the network to estimate the target node position as accurately as possible. As the performance metric, the Cramér-Rao lower bound (CRLB) related to the estimation of the target node position by eavesdropper nodes is derived, and its convexity and monotonicity properties are investigated. By relaxing the integer constraints, the eavesdropper selection problem is approximated by a convex optimization problem and algorithms are proposed for eavesdropper selection. Moreover, in the presence of parameter uncertainty, a robust version of the eavesdropper selection problem is developed. Then, the problem of jammer selection is proposed where the aim is to optimally place a given number of jammer nodes to a subset of possible positions for degrading the localization accuracy of the network as much as possible. A CRLB expression from the literature is used as the performance metric, and its concavity and monotonicity properties are derived. Also, a convex optimization problem and its robust version are derived after relaxation. Moreover, the joint eavesdropper and jammer selection problem is proposed with the goal of placing certain numbers of eavesdropper and jammer nodes to a subset of possible positions. Simulation results are presented to illustrate performance of the proposed algorithms.

show abstract