Improved Energy Detectors for Cognitive Radios With Randomly Arriving or Departing Primary Users
作者： N C Beaulieu , Yunfei Chen
关键词: Artificial neural network 、 Signal-to-noise ratio 、 Electronic engineering 、 Telecommunications 、 Primary (astronomy) 、 Random variable 、 Detector 、 Energy (signal processing) 、 Computer science 、 Sample size determination 、 Cognitive radio
摘要: New and improved energy detectors for cognitive radios are derived by considering the effect of primary user traffic on spectrum sensing. The new designed based assumption that randomly arrives or departs during sensing period. Numerical results show detector outperforms conventional in all cases examined. performance gain depends operating signal-to-noise ratio as well sample size used.
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