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Abstract / Description of output
This letter analyzes the performances of a simple reconstruction method, namely the Projected Back-Projection (PBP), for estimating the direction of a sparse signal from its phase-only (or amplitude-less) complex Gaussian random measurements, i.e., an extension of one-bit compressive sensing to the complex field. To study the performances of this algorithm, we show that complex Gaussian random matrices respect, with high probability, a variant of the Restricted Isometry Property (RIP) relating to the l1 -norm of the sparse signal measurements to their l2 -norm. This property allows us to upper-bound the reconstruction error of PBP in the presence of phase noise. Monte Carlo simulations are performed to highlight the performance of our approach in this phase-only acquisition model when compared to error achieved by PBP in classical compressive sensing.
Original language | English |
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Journal | IEEE Signal Processing Letters |
Volume | 27 |
Early online date | 12 Feb 2020 |
DOIs | |
Publication status | E-pub ahead of print - 12 Feb 2020 |
Keywords / Materials (for Non-textual outputs)
- eess.SP
- cs.IT
- math.IT
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Dive into the research topics of '(l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements'. Together they form a unique fingerprint.Projects
- 1 Finished
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C-SENSE: Exploiting low dimensional models in sensing, computation and signal processing
1/09/16 → 31/08/22
Project: Research