Compressive demodulation of mutually interfering signals

The challenge of Multiuser Detection (MUD) is that of demodulating mutually interfering signals given that at any time instant the number of active users is typically small. The promise of compressed sensing is the demodulation of sparse superpositions of signature waveforms from very few measuremen...

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Bibliographic Details
Published in2012 IEEE Statistical Signal Processing Workshop (SSP) pp. 592 - 595
Main Authors Yao Xie, Yuejie Chi, Applebaum, L., Calderbank, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Coherence
Compressed Sensing
Delay
Demodulation
Gabor Frames
Measurement uncertainty
Multiuser detection
Signal to noise ratio
Vectors
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Summary:The challenge of Multiuser Detection (MUD) is that of demodulating mutually interfering signals given that at any time instant the number of active users is typically small. The promise of compressed sensing is the demodulation of sparse superpositions of signature waveforms from very few measurements. This paper considers signature waveforms that are are drawn from a Gabor frame. It describes a MUD architecture that uses subsampling to convert analog input to a digital signal, and then uses iterative matching pursuit to recover the active users. Compressive demodulation requires K log N samples to recover K active users whereas standard MUD requires N samples. The paper provides theoretical performance guarantees and consistent numerical simulations.
ISBN:9781467301824
1467301825
ISSN:2373-0803
2693-3551
DOI:10.1109/SSP.2012.6319768