Sparsity analysis of FH-BPSK signals via K-SVD dictionary learning

Zhang, Yidong; Yang, Wenge; Cheng, Yongqiang

doi:10.1109/cci.2016.7778932

Cited by 3 publications

(1 citation statement)

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“…It takes the complex baseband samples as input and outputs the estimation delayτ . To achieve a fast synchronisation algorithm (running at F s ), a limited complexity is required and, thus, methods using maximum likelihood [11], wavelet transform [12] or machine learning [13] can not be used. The proposed algorithm relies on Fourier transform to detect the signal hop with a high time resolution.…”

Section: A Proposed Approachmentioning

confidence: 99%

Towards Real Time Interception of Frequency Hopping Signals

Lavaud

Gerzaguet

Gautier

et al. 2020

2020 IEEE Workshop on Signal Processing Systems (SiPS)

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Securing data transmission aims at preventing unauthorized interceptors from accessing sensitive data. To that end, Transmission Security (TRANSEC) defines several security techniques for physical layer and cryptography. Among those techniques, Frequency Hopping (FH) transmission rapidly changes the carrier frequency over many distinct channels, following a predefined pseudo-random sequence of frequency hops. It allows a sporadic communication over a wide bandwidth, being therefore hard to intercept. To tackle this security barrier, this paper proposes a method to intercept the used channel of a FH system, when the system bandwidth is large and the number of hops per second is very high. Both a channel detection and a synchronisation methods are introduced and allow an accurate channel detection after only 20 hops dedicated to synchronisation. Moreover, the proposed method has been validated on real FHbased Bluetooth signal using a software defined radio.

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Section: A Proposed Approachmentioning

confidence: 99%