2011
DOI: 10.1109/jsac.2011.110812
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Identifying Wireless Users via Transmitter Imperfections

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Cited by 197 publications
(110 citation statements)
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“…These AFE imperfections are inevitable variations introduced to different devices during the fabrication of analog components. Several device-specific characteristics, including the in-phase/quadrature imbalance (IQI) [4], the digital-to-analog converter and the power amplifier characteristics [5], as well as the carrier frequency offset (CFO) [6] have been explored for authentication. In practice, the difference of the selected hardware attributes between different devices is usually small, and its observation is further corrupted by both the noise and the interference, which reduces the accuracy of estimating these attributes for authentication purposes.…”
Section: A Low Reliability Of Physical-layer Authenticationmentioning
confidence: 99%
“…These AFE imperfections are inevitable variations introduced to different devices during the fabrication of analog components. Several device-specific characteristics, including the in-phase/quadrature imbalance (IQI) [4], the digital-to-analog converter and the power amplifier characteristics [5], as well as the carrier frequency offset (CFO) [6] have been explored for authentication. In practice, the difference of the selected hardware attributes between different devices is usually small, and its observation is further corrupted by both the noise and the interference, which reduces the accuracy of estimating these attributes for authentication purposes.…”
Section: A Low Reliability Of Physical-layer Authenticationmentioning
confidence: 99%
“…However, the embedding dimension should be determined first, and the amount of data to calculate the NPE should be large if one wants to obtain a relatively reliable statistic. Polak et al identified the unique emitter by modeling the nonlinearity of power amplifier (PA) and integral nonlinearity (INL) of the digital-to-analog converter (DAC) with Volterra series and a Brownian Bridge random process, respectively [21]. Its performance would become worse when these models do not match well with the real signals.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, we can extract the RF fingerprints from received signals from the nonlinear point of view. In consideration of the drawbacks of the aforementioned nonlinear SEI approaches [20][21][22], we will propose a novel nonlinear SEI method based on the natural measure of the one-dimensional component of higher dimensional systems. This method does not need any model, and it is effective in the case of a relatively small amount of data and low sample rate.…”
Section: Introductionmentioning
confidence: 99%
“…However, no evidence for this assumption is available in the literature. Most previously published studies have used either an anechoic chamber or a laboratory environment with high SNR and line-of-sight propagation in the experimental validation of RF fingerprinting techniques [9][10][11][12][13]. Such environments do not represent the typical conditions found in practice, in which transceivers are not of RF test laboratory specification, and channel impairments and interference degrade the unique features embedded in the analog signal of the transmitter.…”
Section: Introductionmentioning
confidence: 99%