COGNITIVE_RADIO

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A Multi-Task Learning Framework for Joint Sub-Nyquist Wideband Spectrum Sensing and Modulation Recognition
《China Communications》2025年第1期128-138,共11页Dong Xin Stefanos Bakirtzis Zhang Jiliang Zhang Jie 
The utilization of millimeter-wave frequencies and cognitive radio(CR)are promising ways to increase the spectral efficiency of wireless communication systems.However,conventional CR spectrum sensing techniques entail...
关键词：automated modulation classification cognitive radio convolutional neural networks deep learning spectrum sensing sub-Nyquist sampling 
Cognitive Jammers Assisted Covert Communication in Cognitive Radio Networks
《China Communications》2024年第9期75-89,共15页Liu Changjun Shi Jia Tie Zhuangzhuang Wang Yongchao 
supported in part by the National Natural Science Foundation of China(No.61941105,No.61901327 and No.62101450);in part by the National Natural Science Foundation for Distinguished Young Scholar(No.61825104);in part by the Fundamental Research Funds for the Central Universities(JB210109);in part by the Foundation of State Key Laboratory of Integrated Services Networks of Xidian University(ISN22-03)。
In this work,we investigate the covert communication in cognitive radio(CR)networks with the existence of multiple cognitive jammers(CJs).Specifically,the secondary transmitter(ST)helps the primary transmitter(PT)to r...
关键词：cognitive jammer cognitive radio covert communication performance analysis 
Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning
《China Communications》2024年第6期53-68,共16页Zhang Zhenyu Zhang Yong Yuan Siyu Cheng Zhenjie 
supported by the National Natural Science Foundation of China(Grant No.61971057).
In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Se...
关键词：cognitive radio deep reinforcement learning network slicing power-domain non-orthogonal multiple access resource allocation 
Cross-Band Spectrum Prediction Algorithm Based on Data Conversion Using Generative Adversarial Networks
《China Communications》2023年第10期136-152,共17页Chuang Peng Rangang Zhu Mengbo Zhang Lunwen Wang 
supported by the fund coded,National Natural Science Fund program(No.11975307);China National Defence Science and Technology Innovation Special Zone Project(19-H863-01-ZT-003-003-12).
Spectrum prediction is one of the new techniques in cognitive radio that predicts changes in the spectrum state and plays a crucial role in improving spectrum sensing performance.Prediction models previously trained i...
关键词：cognitive radio cross-band spectrum prediction deep learning generative adversarial network 
Resource Allocation and Trajectories Design for UAV-Assisted Jamming Cognitive UAV Networks被引量：3
《China Communications》2022年第5期206-217,共12页Zhenhui Tao Fuhui Zhou Yuhao Wang Xiaodong Liu Qihui Wu 
This work was supported in part by the National Natural Science Foundation of China(No.62031012,62071223,and 62061030);in part by the National Key Research and Development Project of China(2018YFB1404303,2018YFB14043033,and 2020YFB1807602);in part by the National Key Scientific Instrument and Equipment Development Project(61827801);in part by the Open Project of the Shaanxi Key Laboratory of Information Communication Network and Security(ICNS201701);by Young Elite Scientist Sponsorship Program by CAST,and by Graduate Innovation Foundation of Jiangxi Province(YC2019-S0350).
Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity problem.Cognitive UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdro...
关键词：cognitive radio unmanned aerial vehicles communications physical layer security cooperative jamming 
Primary User Adversarial Attacks on Deep Learning-Based Spectrum Sensing and the Defense Method被引量：4
《China Communications》2021年第12期94-107,共14页Shilian Zheng Linhui Ye Xuanye Wang Jinyin Chen Huaji Zhou Caiyi Lou Zhijin Zhao Xiaoniu Yang 
the National Nat-ural Science Foundation of China under Grant No.62072406,No.U19B2016,No.U20B2038 and No.61871398;the Natural Science Foundation of Zhejiang Province under Grant No.LY19F020025;the Major Special Funding for“Science and Tech-nology Innovation 2025”in Ningbo under Grant No.2018B10063.
The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been verified.In this paper,we propose primary user adversarial attack(PUAA)to verify the rob...
关键词：spectrum sensing cognitive radio deep learning adversarial attack autoencoder DEFENSE 
An Overview of Wireless Communication Technology Using Deep Learning被引量：7
《China Communications》2021年第12期1-36,共36页Jiyu Jiao Xuehong Sun Liang Fang Jiafeng Lyu 
the National Nat-ural Science Foundation of China under Grant No.62061039;Postgraduate Innovation Project of Ningxia University No.JIP20210076;Key project of Ningxia Natural Science Foundation No.2020AAC02006.
with the development of 5G,the future wireless communication network tends to be more and more intelligent.In the face of new service de-mands of communication in the future such as super-heterogeneous network,multipl...
关键词：artificial intelligence wireless communi�cation deep learning cognitive radio edge comput�ing channel measurement end-to-end encoder and decoder visible light communication 
Spectrum Sensing via Temporal Convolutional Network被引量：7
《China Communications》2021年第9期37-47,共11页Tao Ni Xiaojin Ding Yunfeng Wang Jun Shen Lifeng Jiang Gengxin Zhang 
the National Science Foundation of China (No.91738201, 61971440);the Jiangsu Province Basic Research Project (No.BK20192002);the China Postdoctoral Science Foundation (No.2018M632347);the Natural Science Research of Higher Education Institutions of Jiangsu Province (No.18KJB510030)。
In this paper,we investigate a spectrumsensing system in the presence of a satellite,where the satellite works as a sensing node.Considering the conventional energy detection method is sensitive to the noise uncertain...
关键词：cognitive radio spectrum sensing deep learning temporal convolutional network satellite communication 
Joint 3D Trajectory and Resource Optimization for A UAV Relay-Assisted Cognitive Radio Network被引量：7
《China Communications》2021年第6期184-200,共17页Zhen Wang Fuhui Zhou Yuhao Wang Qihui Wu 
This work was supported by the National Key Research and Development Project under Grant 2020YFB1807602,Natural Science Foundation of China under Grant 62071223,62031012,61701214 and 61661028;by the National Key Scientific Instrument and Equipment Development Project under Grant No.61827801;the Open Project of the Shaanxi Key Laboratory of Information Communication Network and Security under Grant ICNS201701;the Excellent Youth Foundation of Jiangxi Province under Grant 2018ACB21012 and in part by the Young Elite Scientist Sponsorship Program by CAST.
In this paper,we consider a new spectrum sharing scenario for a cognitive relay network,where a secondary unmanned aerial vehicle(UAV)relay receives information from the ground secondary base station(SBS)and transmits...
关键词：cognitive radio UAV communication 3D trajectory design mobile relaying power allocation 
Energy-Efficient Power Allocation for IoT Devices in CR-NOMA Networks被引量：3
《China Communications》2021年第4期166-181,共16页Guangfu Wu Wenyi Zheng Yun Li Mengyuan Zhou 
supported in part by the Science and Technology Research Program of the National Science Foundation of China(No.61671096);Chongqing Research Program of Basic Science and Frontier Technology(No.cstc2017jcyj BX0005);Chongqing Municipal Education Commission(No.KJQN201800642);Doctoral Student Training Program(No.BYJS2016009)。
Non-orthogonal multiple access is a promising technique to meet the harsh requirements for the internet of things devices in cognitive radio networks.To improve the energy efficiency(EE)of the unlicensed secondary use...
关键词：cognitive radio-non-orthogonal multiple access(CR-NOMA) power allocation energy efficiency internet of things(IoT) 
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