Adaptive Cooperative Spectrum Sensing Based on SNR Estimation in Cognitive Radio Networks
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초록
Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and otherunfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracyand reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimatedsignal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED)is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a bettersensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNRwith low complexity. The local sensing node transmits the perceived results through the control channel to thefusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth iseffectively saved. Simulation results show that the proposed scheme can effectively improve the systemdetection probability, shorten the average sensing time, and has better robustness without largely increasingthe costs of sensing system.
Abstract
Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and otherunfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracyand reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimatedsignal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED)is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a bettersensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNRwith low complexity. The local sensing node transmits the perceived results through the control channel to thefusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth iseffectively saved. Simulation results show that the proposed scheme can effectively improve the systemdetection probability, shorten the average sensing time, and has better robustness without largely increasingthe costs of sensing system.
참고문헌 (16)
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