Non-Uniform Wavelet Sampling for RF Analog-to-Information Conversion
| Autor: | Michael Pelissier, Christoph Studer |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Spectrum sensing
FOS: Computer and information sciences Computer science Computer Science - Information Theory Cognitive radio 02 engineering and technology Wavelets Wavelet Sampling (signal processing) Aliasing Analog-to-information (A2I) conversion 0202 electrical engineering electronic engineering information engineering Electronic engineering Electrical and Electronic Engineering Wideband Radio-frequency (RF) signal acquisition Noise (signal processing) Information Theory (cs.IT) Compressive sensing Internet of Things (IoT) 020208 electrical & electronic engineering 020206 networking & telecommunications Compressed sensing Radio frequency Energy (signal processing) |
| Zdroj: | IEEE Transactions on Circuits and Systems I: Regular Papers, 65 (2) |
| ISSN: | 1558-0806 1549-8328 1057-7122 |
| Popis: | Feature extraction, such as spectral occupancy, interferer energy and type, or direction-of-arrival, from wideband radio-frequency (RF) signals finds use in a growing number of applications as it enhances RF transceivers with cognitive abilities and enables parameter tuning of traditional RF chains. In power and cost limited applications, e.g., for sensor nodes in the Internet of Things, wideband RF feature extraction with conventional, Nyquist-rate analog-to-digital converters is infeasible. However, the structure of many RF features (such as signal sparsity) enables the use of compressive sensing (CS) techniques that acquire such signals at sub-Nyquist rates; while such CS-based analog-to-information (A2I) converters have the potential to enable low-cost and energy-efficient wideband RF sensing, they suffer from a variety of real-world limitations, such as noise folding, low sensitivity, aliasing, and limited flexibility. This paper proposes a novel CS-based A2I architecture called non-uniform wavelet sampling. Our solution extracts a carefully-selected subset of wavelet coefficients directly in the RF domain, which mitigates the main issues of existing A2I converter architectures. For multi-band RF signals, we propose a specialized variant called non-uniform wavelet bandpass sampling (NUWBS), which further improves sensitivity and reduces hardware complexity by leveraging the multi-band signal structure. We use simulations to demonstrate that NUWBS approaches the theoretical performance limits of l1 -norm-based sparse signal recovery. We investigate hardware-design aspects and show ASIC measurement results for the wavelet generation stage, which highlight the efficacy of NUWBS for a broad range of RF feature extraction tasks in cost- and power-limited applications. IEEE Transactions on Circuits and Systems I: Regular Papers, 65 (2) ISSN:1549-8328 ISSN:1057-7122 ISSN:1558-0806 |
| Databáze: | OpenAIRE |
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