Feature-based compressive signal processing (CSP) measurement design for the pattern analysis of Cognitive Radio spectrum

@article{Guo2013FeaturebasedCS,
  title={Feature-based compressive signal processing (CSP) measurement design for the pattern analysis of Cognitive Radio spectrum},
  author={Mengcheng Guo and Fei Hu and Yeqing Wu and Sunil Kumar and John D. Matyjas},
  journal={2013 IEEE Global Communications Conference (GLOBECOM)},
  year={2013},
  pages={1131-1136}
}
Cognitive Radio (CR) can efficiently utilize the licensed wideband spectrum whenever the primary users (PUs) are absent. Spectrum sensing is the first step and an important function to fulfill the CR system. A cyclostationary feature detector can robustly detect the PU's modulated signals even under strong interferences. However this detector needs high signal sampling rate and also puts heavy computation burden on the system. Compressive sensing (CS) can compress the data at the front sampling… CONTINUE READING

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