A Spectrum Regeneration and Demodulation Method for Multiple Direct Undersampled Real Signals

We propose a spectrum regeneration and demodulation method for multiple direct RF undersampled real signals by using a new algorithm. Many methods have been proposed to regenerate the RF spectrum by using undersampling because of its simple circuit architecture. However, it is difficult to regenerat...

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Veröffentlicht in:IEICE Transactions on Communications 2021/10/01, Vol.E104.B(10), pp.1260-1267
Hauptverfasser: SHIBA, Takashi, FURUICHI, Tomoyuki, MOTOYOSHI, Mizuki, KAMEDA, Suguru, SUEMATSU, Noriharu
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container_issue 10
container_start_page 1260
container_title IEICE Transactions on Communications
container_volume E104.B
creator SHIBA, Takashi
FURUICHI, Tomoyuki
MOTOYOSHI, Mizuki
KAMEDA, Suguru
SUEMATSU, Noriharu
description We propose a spectrum regeneration and demodulation method for multiple direct RF undersampled real signals by using a new algorithm. Many methods have been proposed to regenerate the RF spectrum by using undersampling because of its simple circuit architecture. However, it is difficult to regenerate the spectrum from a real signal that has a band wider than a half of the sampling frequency, because it is difficult to include complex conjugate relation of the folded spectrum into the linear algebraic equation in this case. We propose a new spectrum regeneration method from direct undersampled real signals that uses multiple clocks and an extended algorithm considering the complex conjugate relation. Simulations are used to verify the potential of this method. The validity of the proposed method is verified by using the simulation data and the measured data. We also apply this algorithm to the demodulation system.
doi_str_mv 10.1587/transcom.2020DSP0006
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subjects Algorithms
Circuits
Clocks
compressed sensing
Conjugates
Demodulation
direct undersampling
IoT
Linear algebra
real signal
Regeneration
spectrum regeneration
sub-nyquist
title A Spectrum Regeneration and Demodulation Method for Multiple Direct Undersampled Real Signals
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