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- W2370655162 abstract "A distributed probabilistic Bayesian compressed spectrum sensing algorithm(PBCS) is proposed based on Gaussian process to improve the detection performance of compressed spectrum sensing under low signal to noise ratio condition in wideband cognitive radio networks.A hierarchical normal distribution probabilistic model is applied to represent the compressed spectrum reconstruction.The model parameters are exchanged among the cognitive radios as cooperation information,and then are utilized to implement compressed spectrum sensing based on the local compressed sensing data.Being different from existing cooperative spectrum sensing methods,where the final sensing decisions or the rough sensing data are used as the cooperation information,model parameters fusion is conveyed among the cognitive radios in the proposed PBCS algorithm.Therefore,the negative effectiveness from those cooperated neighbors experiencing low signal to noise ratio sensing environment is effectively reduced and the detection performance is improved.Simulations show that PBCS achieves a detection rate over 0.9 while false alarm remains 0.1 when signal to noise ratio is-5 dB." @default.
- W2370655162 created "2016-06-24" @default.
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- W2370655162 date "2011-01-01" @default.
- W2370655162 modified "2023-09-24" @default.
- W2370655162 title "A Sensing Algorithm Based on Distributed Cooperative Compressed Spectrum for Wideband Cognitive Radio Networks" @default.
- W2370655162 hasPublicationYear "2011" @default.
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