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...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,multiple communication sce-narios,large number of antenna elements and large bandwidth,new theories and technologies of intelli-gent communication have been widely studied,among which Deep Learning(DL)is a powerful technology in artificial intelligence(AI).It can be trained to con-tinuously learn to update the optimal parameters.This paper reviews the latest research progress of DL in in-telligent communication,and emphatically introduces five scenarios including Cognitive Radio(CR),Edge Computing(EC),Channel Measurement(CM),End to end Encoder/Decoder(EED)and Visible Light Com-munication(VLC).The prospect and challenges of further research and development in the future are also discussed.展开更多
Software defined radio(SDR)is a wireless communication technology that uses modern software to control the traditional“pure hardware circuit”.It can provide an effective and secure solution to the problem of buildin...Software defined radio(SDR)is a wireless communication technology that uses modern software to control the traditional“pure hardware circuit”.It can provide an effective and secure solution to the problem of building multi-mode,multi-frequency and multifunction wireless communication equipment.Although the concept and application of SDR have been studied a lot,there is little discussion about the operating efficiency of the established system.For the purpose of shortening the delay of mapping and reducing the high computing load in the cloud,a radio monitoring system based on edge computing is developed to achieve the flexible,extensible and real-time monitoring of high-performance SDR applications.To promote the edge intelligence of deep learning(DL)service deployment through edge computing(EC),we developed an edge intelligence algorithm of convolutional neural network(CNN)based on attention mechanism to carry out modulation recognition(MR)of the edge signal and make MR closer to the antenna terminal.Through the experiment of the system and the edge algorithm,this thesis verifies the effectiveness of the developed multifunction radio signal monitoring system.展开更多
基金the National Nat-ural Science Foundation of China under Grant No.62061039Postgraduate Innovation Project of Ningxia University No.JIP20210076Key project of Ningxia Natural Science Foundation No.2020AAC02006.
文摘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,multiple communication sce-narios,large number of antenna elements and large bandwidth,new theories and technologies of intelli-gent communication have been widely studied,among which Deep Learning(DL)is a powerful technology in artificial intelligence(AI).It can be trained to con-tinuously learn to update the optimal parameters.This paper reviews the latest research progress of DL in in-telligent communication,and emphatically introduces five scenarios including Cognitive Radio(CR),Edge Computing(EC),Channel Measurement(CM),End to end Encoder/Decoder(EED)and Visible Light Com-munication(VLC).The prospect and challenges of further research and development in the future are also discussed.
基金supported by the National Natural Science Foundation of China under Grant 62061039in part by Key project of Ningxia Natural Science Foundation under Grant 2020AAC02006.
文摘Software defined radio(SDR)is a wireless communication technology that uses modern software to control the traditional“pure hardware circuit”.It can provide an effective and secure solution to the problem of building multi-mode,multi-frequency and multifunction wireless communication equipment.Although the concept and application of SDR have been studied a lot,there is little discussion about the operating efficiency of the established system.For the purpose of shortening the delay of mapping and reducing the high computing load in the cloud,a radio monitoring system based on edge computing is developed to achieve the flexible,extensible and real-time monitoring of high-performance SDR applications.To promote the edge intelligence of deep learning(DL)service deployment through edge computing(EC),we developed an edge intelligence algorithm of convolutional neural network(CNN)based on attention mechanism to carry out modulation recognition(MR)of the edge signal and make MR closer to the antenna terminal.Through the experiment of the system and the edge algorithm,this thesis verifies the effectiveness of the developed multifunction radio signal monitoring system.
