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تسجيل مستخدم جديدRecent Advances on Sub-Nyquist Sampling-Based Wideband Spectrum Sensing
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Cognitive radio (CR) is a promising technology enabling efficient utilization of the spectrum resource for future wireless systems. As future CR networks are envisioned to operate over a wide frequency range, advanced wideband spectrum sensing (WBSS) capable of quickly and reliably detecting idle spectrum bands across a wide frequency span is essential. In this article, we provide an overview of recent advances on sub-Nyquist sampling-based WBSS techniques, including compressed sensing-based methods and compressive covariance sensing-based methods. An elaborate discussion of the pros and cons of each approach is presented, along with some challenging issues for future research. A comparative study suggests that the compressive covariance sensing-based approach offers a more competitive solution for reliable real-time WBSS.
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We present a mixed analog-digital spectrum sensing method that is especially suited to the typical wideband setting of cognitive radio (CR). The advantages of our system with respect to current architectures are threefold. First, our analog front-end
is fixed and does not involve scanning hardware. Second, both the analog-to-digital conversion (ADC) and the digital signal processing (DSP) rates are substantially below Nyquist. Finally, the sensing resources are shared with the reception path of the CR, so that the lowrate streaming samples can be used for communication purposes of the device, besides the sensing functionality they provide. Combining these advantages leads to a real time map of the spectrum with minimal use of mobile resources. Our approach is based on the modulated wideband converter (MWC) system, which samples sparse wideband inputs at sub-Nyquist rates. We report on results of hardware experiments, conducted on an MWC prototype circuit, which affirm fast and accurate spectrum sensing in parallel to CR communication.
Introduction of spectrum-sharing in 5G and subsequent generation networks demand base-station(s) with the capability to characterize the wideband spectrum spanned over licensed, shared and unlicensed non-contiguous frequency bands. Spectrum character
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Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper, we consider the challenging problem of blind sub-Nyquist sampling of multiband signals, whose unknown frequency support
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