Wavelet denoising of signals based on the fourth order moment

Hippenstiel, Ralph D.; Mantis, S.

doi:10.1109/isspa.2001.949853

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…The first RF fingerprinting system was used in the Vietnam War to differentiate between a friendly and foe radar (Nansai Hu, 2012). In the past few years, researchers explored many RF fingerprinting techniques for identification of transmitters in commercial spheres (Marcus, 1992;Hippenstiel and Payal, 1996;Xu, et al, 2008;Toonstra and Kinsner, 2002;Zamora, et al, 2010). One such example is in cellular industry, where RF fingerprinting is used to prevent cell phone cloning (Kaplan and Stanhope, 1999;Hoogerwerf, et al, 2000).…”

Section: Physical Layer Securitymentioning

confidence: 99%

An Overview of Radio Frequency Fingerprinting for Low-End Devices

Rehman

Alam

Ardekani

2014

International Journal of Mobile Computing and Multimedia Communications

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RF fingerprinting is proposed as a means of providing an additional layer of security for wireless devices. A masquerading or impersonation attacks can be prevented by establishing the identity of wireless transmitter using unique transmitter RF fingerprint. Unique RF fingerprints are attributable to the analog components (digital-to-analog converters, band-pass filters, frequency mixers and power amplifiers) present in the RF front ends of transmitters. Most of the previous researches have reported promising results with an accuracy of up to 99% using high-end receivers (e.g. Giga-sampling rate oscilloscopes, spectrum and vector signal analysers) to validate the proposed techniques. However, practical implementation of RF fingerprinting would require validation with low-end (low-cost) devices that also suffers from impairments due to the presence of analog components in the front end of its receiver. This articles provides the analysis and implementation of RF fingerprinting using low-cost receivers and challenges associated with it.

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Section: Physical Layer Securitymentioning

confidence: 99%

An Overview of Radio Frequency Fingerprinting for Low-End Devices

Rehman

Alam

Ardekani

2014

International Journal of Mobile Computing and Multimedia Communications

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“…Several techniques were proposed in the literature. In our work, we propose to use the fourth order moment threshold given in [9] and improved in [10]. This thresholding is based on the analysis of AWGN noise according to its fourth order moment and is done as follows [10]:…”

Section: B) Thresholdingmentioning

confidence: 99%

Wavelet denoising in cooperative and NonCooperative spectrum sensing

2013

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Cognitive Radio has become an effective solution for the scarcity and the inefficient use of the spectrum. The performance of the cognitive radio (CR) system depends however on how well it can maximize the usage of the free bands without causing interference to primary users. The ability to detect the primary user in CR systems relies on Spectrum Sensing (SS). In this paper we propose a method to improve the performance of Energy Detection SS using Wavelet Denoising. Cooperative and non-cooperative sensing scenarios are considered. Results show that sensing accuracy can be highly improved in the cooperative scenario when the leaves of the tree of wavelet packet transform are used as a basis for denoising. Different mother wavelets are also tested. Simulation results are analyzed and are compared to traditional results.

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Wavelet denoising of signals based on the fourth order moment

Cited by 2 publications

References 5 publications

An Overview of Radio Frequency Fingerprinting for Low-End Devices

An Overview of Radio Frequency Fingerprinting for Low-End Devices

Wavelet denoising in cooperative and NonCooperative spectrum sensing

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