Error minimizing jammer localization through smart estimation of ambient noise

Liu, Zhenhua; Liu, Hongbo; Xu, Wenyuan; Chen, Yingying

doi:10.1109/mass.2012.6502530

Cited by 11 publications

(7 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the jamming power cannot be derived or estimated directly. In order to solve this problem, the jamming power is assumed to be chosen from a series of discrete values, which is also the assumption made in [24]. The proposed localization algorithm will be conducted under these discrete jamming powers and the best position and optimal value under each jamming power will be recorded.…”

Section: Discussionmentioning

confidence: 99%

Jammer Localization in Multihop Wireless Networks Based on Gravitational Search

Wang

Wei²,

Jiang³

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

Multihop Wireless Networks (MHWNs) can be easily attacked by the jammer for their shared nature and open access to the wireless medium. The jamming attack may prevent the normal communication through occupying the same wireless channel of legal nodes. It is critical to locate the jammer accurately, which may provide necessary message for the implementation of antijamming mechanisms. However, current range-free methods are sensitive to the distribution of nodes and parameters of the jammer. In order to improve the localization accuracy, this article proposes a jammer localization method based on Gravitational Search Algorithm (GSA), which is a heuristic optimization evolutionary algorithm based on Newton’s law of universal gravitation and mass interactions. At first, the initial particles are selected randomly from the jammed area. Then, the fitness function is designed based on range-free method. At each iteration, the mass and position of the particles are updated. Finally, the position of particle with the maximum mass is considered as the estimated jammer’s position. A series of simulations are conducted to evaluate our proposed algorithms and the simulation results show that the GSA-based localization algorithm outperforms many state-of-the-art algorithms.

show abstract

Section: Discussionmentioning

confidence: 99%

Jammer Localization in Multihop Wireless Networks Based on Gravitational Search

Wang

Wei²,

Jiang³

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…The detection of physical layer jammers is done via hardware-assisted approaches and statistical indices methods. In [3], [7], the affected nodes detect the constant jammer by sensing the strength of the jamming signal (JSS). They also report their measurements to a designated node in wireless networks.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks

Abdollahi

Malekinasab

et al. 2021

2021 IEEE 46th Conference on Local Computer Networks (LCN)

View full text Add to dashboard Cite

An active jammer could severely degrade the communication quality for wireless networks. Since all wireless nodes openly access the shared media, the harsh effects are exaggerated by retransmission attempts of affected devices. Fast and precise detection of the jammer is of vital importance for heterogeneous wireless environments such as the Internet of things (IoT). It could activate a series of corrective countermeasures to ensure the robust operation of the network. In this paper, we propose a local, straightforward, and numerical metric called the number of jammed slots (NJS), by which we can quickly detect the presence of a jammer and identify the jammed nodes at the software level in broadcast networks. NJS calculation is carried out by a central node which collects the MAC-layer statuses of all wireless nodes in a periodical fashion. Our simulation results indicate that NJS outperforms current detection methods in terms of accuracy and precision.

show abstract

“…Adding z 3 2 to both sides of the inequality in (22), and rearranging the terms, the following distance relation is achieved: Point z2 is the projection of z1 onto H.…”

Section: Propositionmentioning

confidence: 99%

“…Adding z 3 2 to both sides of the inequality in (22), and rearranging the terms, the following distance relation is achieved: for all z 3 ∈ H. Hence, for any point z 1 outside H, its projection onto H, denoted by z 2 , is closer to any point z 3 on H. Therefore, the optimal jammer location cannot be outside the convex hull H formed by the locations of the target nodes as the CRLB for each target node is inversely proportional to the distance between the jammer and the target nodes.…”

Section: Remarkmentioning

confidence: 99%

Optimal Jammer Placement in Wireless Localization Systems

Gezici

Bayram

Kurt

et al. 2016

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

In this study, the optimal jammer placement problem is proposed and analyzed for wireless localization systems. In particular, the optimal location of a jammer node is obtained by maximizing the minimum of the Cramer-Rao lower bounds (CRLBs) for a number of target nodes under location related constraints for the jammer node. For scenarios with more than two target nodes, theoretical results are derived to specify conditions under which the jammer node is located as close to a certain target node as possible, or the optimal location of the jammer node is determined by two of the target nodes. Also, explicit expressions are provided for the optimal location of the jammer node in the presence of two target nodes. In addition, in the absence of distance constraints for the jammer node, it is proved, for scenarios with more than two target nodes, that the optimal jammer location lies on the convex hull formed by the locations of the target nodes and is determined by two or three of the target nodes, which have equalized CRLBs. Numerical examples are presented to provide illustrations of the theoretical results in different scenarios.Comment: To appear in IEEE Transactions on Signal Processin

show abstract

Error minimizing jammer localization through smart estimation of ambient noise

Cited by 11 publications

References 23 publications

Jammer Localization in Multihop Wireless Networks Based on Gravitational Search

Jammer Localization in Multihop Wireless Networks Based on Gravitational Search

An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks

Optimal Jammer Placement in Wireless Localization Systems

Contact Info

Product

Resources

About