Jamming detection and SNR/SNJR estimation

Tsang, Chit-Sang

doi:10.1109/aero.2011.5747345

Cited by 7 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [7], for jamming detection and mitigation, authors have proposed a protocol that allows each receiver to cooperate with the transmitter, in order to detect any jamming that affects the receiver. Authors in [8] presented a receiver structure that estimates the Signal to Noise plus Jammer Ratio (SNJR) and detects the start and end times of the jammer signals. Then they showed that the performance of the jamming detection is affected by the performance of the SNJR estimation process.…”

Section: Introductionmentioning

confidence: 99%

A support vector machine based algorithm for jamming attacks detection in cellular networks

Jahanshahi

Ghorashi

Eslami

2011

2011 Wireless Advanced

View full text Add to dashboard Cite

In this paper, a support vector machine algorithm is proposed for jamming detection at the base station in cellular networks. The proposed jamming detection process uses only inherent information which is available in common receivers and does not need excessive hardware requirements for external information. Support vector machine algorithm is used in jamming detection process to improve the performance of the jamming detection algorithm and to reduce the required hardware complexity. The performance of the proposed algorithm is modeled in a TETRA network and simulation results show acceptable results in a wide range of user terminal velocities with comparison to other conventional methods.

show abstract

Section: Introductionmentioning

confidence: 99%

A support vector machine based algorithm for jamming attacks detection in cellular networks

Jahanshahi

Ghorashi

Eslami

2011

2011 Wireless Advanced

View full text Add to dashboard Cite

show abstract

An Integrated Approach for Jammer Detection using Software Defined Radio

Bhojani¹,

Joshi²

2016

Procedia Computer Science

View full text Add to dashboard Cite

Utilizing support vector machine and fuzzy C-means algorithms in the base station for jamming detection

Jahanshahi

Ghorashi

Eslami

2013

Journal of the Chinese Institute of Engineers

View full text Add to dashboard Cite

This study presents a comparison of two proposed jamming detection algorithms based on fuzzy C-means (FCM) and support vector machine (SVM) algorithms. Since the SVM classification algorithm needs to be trained for a short period of time before implementation, to improve the performance of the FCM-based jamming detection algorithm, a convenient Doppler shift estimation algorithm has been used in order to recognize the information in the channel. The jamming detection process uses only inherent information which is available in common receivers without any excessive hardware requirements. Using SVM-and FCM-based jamming detection algorithms not only improves the performance of jamming detection, but also reduces hardware complexity. The performance of the proposed algorithms in a TETRA network is modeled and simulations show acceptable results over a wide range of user terminal velocities with comparison to conventional methods.

show abstract

Jamming detection and SNR/SNJR estimation

Cited by 7 publications

References 4 publications

A support vector machine based algorithm for jamming attacks detection in cellular networks

A support vector machine based algorithm for jamming attacks detection in cellular networks

An Integrated Approach for Jammer Detection using Software Defined Radio

Utilizing support vector machine and fuzzy C-means algorithms in the base station for jamming detection

Contact Info

Product

Resources

About