Low Probability Of Intercept Communication Based On Structured Radio Beams Using Machine Learning

Information is the characteristic of The Times in today's society.It is an important direction of national science and technology development to occupy the commanding heights of information,continuously improve the security of information and the ability to exchange information quickly.Orbital angular momentum(OAM),as a basic property of electromagnetic wave besides amplitude,phase and polarization,characterizes the spatial structure of electromagnetic wave and has a broad application prospect in wireless communication,radar detection and other fields due to its helical phase distribution.The combination of OAM modes brings abundant structural characteristics to the beam and lays a physical foundation for the signal security coding in the physical layer.The powerful data-based learning capability of machine learning technology can be used to decode and demodulate signals,and its end-to-end characteristics can greatly simplify the complex signal processing process.Firstly,the beamforming technology and beam characteristics of superposed plane spiral OAM(PS-OAM)beams are studied,and a signal coding scheme based on structural radio wave is designed.Then,the machine learning modeling method of signal decoding is studied,and a signal decoding scheme based on machine learning is designed.Finally,a low probability of intercept communication system based on structured radio beams using machine learning is designed and a series of simulation experiments are carried out.The results show that the communication system can achieve an accuracy of over 99.5% using the support vector machine(SVM)model,while the interception accuracy based on clustering model is lower than 70% in different directions.In addition,the multi-array receiving scheme can further improve the communication efficiency,while the inevitable delay characteristic of clustering scheme makes the system security further improved.In summary,the low probability of intercept communication scheme based on structured radio beams using machine learning we proposed can realize secure communication in point-to-point stable new arrival scenarios.