COOPERATIVE SPECTRUM SENSING ALGORITHM BASED ON BAYESIAN OPTIMIZED XGBOOST
In order to improve the spectrum sensing performance of the wireless channel environment,a cooperative spectrum sensing algorithm based on Bayesian optimization XGBoost is proposed.In a cooperative spectrum sensing scenario of a primary user(PU)and three secondary users(SU),the normalized energy characteristics of the signal were extracted.The Bayesian optimization algorithm was used to optimize multiple hyperparameters of the XGBoost model at the same time,and the optimized XGBoost algorithm was used to realize the classification of the signal to be detected.The simulation results show that compared with traditional spectrum sensing algorithms and machine learning algorithms such as KNN,GNB,SVM,MLP,the detection accuracy of this algorithm under Rayl and AWGN channel are 88.4％and 90.25％,respectively,which can effectively improve the cooperative spectrum sensing performance in different channel environments.
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