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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Feng Xi Shengyao Chen Zhong Liu |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Electronic Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PRC (Feng Xi; Shengyao Chen; Zhong Liu) |
| Abstract | Quadrature sampling is an effective technique for extracting digital in-phase and quadrature (I/Q) components in the modulated radio signals. Existing quadrature sampling techniques require the sampling rate to be at least twice of the bandwidth of the bandpass signal. The newly introduced compressive sampling theory makes sampling the analog signal at a low sampling rate possible if the signal has a sparse representation. This paper merges the two sampling techniques and develops a quadrature compressive sampling (QuadCS) system to obtain the digital I/Q components with low-rate samplers. The operation principle of the QuadCS system is described and the formulation to recover the I/Q components from the low-rate samples is developed. The simulation results demonstrate that the QuadCS is effective for acquiring and reconstructing the I/Q components sparse in waveform-matched dictionary. With the QuadCS system, the simulated signals can be sampled at about 10% Nyquist sampling rates. In addition, the output signal-to-noise ratio is improved about 15–20dB. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 697314 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781457710094 |
| e-ISBN | 9781457710100 |
| e-ISBN | 9781457710087 |
| DOI | 10.1109/WCSP.2011.6096838 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-11-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Radar echo signal Baseband Dictionaries Quadrature sampling Radar Bandwidth Sparse signal Noise measurement Compressive sampling Demodulation Signal to noise ratio |
| Content Type | Text |
| Resource Type | Article |
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