计算机应用与软件2024，Vol.41Issue(7)：121-127,7.DOI:10.3969/j.issn.1000-386x.2024.07.019
基于贝叶斯优化XGBoost的协作频谱感知算法
COOPERATIVE SPECTRUM SENSING ALGORITHM BASED ON BAYESIAN OPTIMIZED XGBOOST
摘要
Abstract
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.关键词
认知无线电/频谱感知/贝叶斯优化/XGBoostKey words
Cognitive radio/Spectrum sensing/Bayesian optimization/XGBoost分类
计算机与自动化引用本文复制引用
胡延飞,郭滨,孙佳楠..基于贝叶斯优化XGBoost的协作频谱感知算法[J].计算机应用与软件,2024,41(7):121-127,7.基金项目
吉林省科技发展计划项目(20200404216YY). （20200404216YY）
