Blind Central-Symmetry-Based Feature Detection for Spatial Spectrum Sensing
نویسندگان
چکیده
منابع مشابه
Compressed sensing based cyclic feature spectrum sensing for cognitive radios
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Spectrum sensing is a key technique in cognitive radio networks (CRNs), which enables cognitive radio nodes to detect the unused spectrum holes for dynamic spectrum access. In practice, only a small part of spectrum is occupied by the primary users. Too high sampling rate can cause immense computational costs and sensing problem. Based on sparse representation of signals in the frequency domain...
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Spectrum sensing is the major challenge in the cognitive radio (CR). We propose to learn local feature and use it as the prior knowledge to improve the detection performance. We define the local feature as the leading eigenvector derived from the received signal samples. A feature learning algorithm (FLA) is proposed to learn the feature blindly. Then, with local feature as the prior knowledge,...
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ژورنال
عنوان ژورنال: IEEE Transactions on Vehicular Technology
سال: 2016
ISSN: 0018-9545,1939-9359
DOI: 10.1109/tvt.2016.2550608