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Reducing the Analog and Digital Bandwidth Requirements of RF Receivers for Measuring Periodic Sparse Waveforms
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
Vrije Universiteit Brussel, ELEC department.
University of Gävle, Radio center for measurement technology.
Vrije Universiteit Brussel, ELEC department.
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2012 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 61, no 11, 2960-2971 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, a prototype setup for measuring wideband periodic waveforms whose bandwidth surpasses the analog bandwidth of a radio-frequency receiver is presented. Three major challenges arise in the analog-to-digital stage when measuring such wideband waveforms: the availability of a high sampling rate based on a good amplitude resolution; the availability of the required analog bandwidth to capture the full waveform; and achieving the previous requirements in a cheap way. Those challenges are more pronounced when using wideband modulated signals to test nonlinear devices and when measuring/sensing wideband spectra for cognitive radio applications. For periodic signals, undersampling techniques based on the evolved harmonic sampling can be used to reduce the sampling rate requirements while satisfying a good amplitude resolution. For sparse signals, a technique based on channelization and signal separation is proposed. This technique splits the spectrum of the waveform into parallel channels, downconverts them to the analog frequency band of the analog-to-digital converter (ADC), spreads the channel information, sums them, and then digitizes with a single ADC. Using reconstruction algorithms based on l(1)-norm minimization, the information of the parallel channels can be separated. The original wideband spectrum can be then reconstructed after de-embedding of the channelization process.

Place, publisher, year, edition, pages
2012. Vol. 61, no 11, 2960-2971 p.
Keyword [en]
Channelization, harmonic sampling, l(1)-norm minimization, radio-frequency (RF) measurement systems, signal separation, sparse signals, spectrum reconstruction
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-70005DOI: 10.1109/TIM.2012.2203729ISI: 000309866500013Scopus ID: 2-s2.0-84867576623OAI: oai:DiVA.org:kth-70005DiVA: diva2:485740
Funder
ICT - The Next Generation
Note

QC 20121127

Available from: 2012-01-30 Created: 2012-01-30 Last updated: 2017-12-08Bibliographically approved

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Händel, Peter

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