Adaptive Control Of Space Wireless Laser Channel Based On Artificial Intelligence

In recent years,in order to meet the growing all-time global spaceground integrated communication capability,it is urgent to improve the data transmission capability of the communication system.High speed and reliable transmission have become the main measurement factors.Satellite laser communication has the characteristics of transmitting massive data at a high rate,which has become the focus of research in the field of communication.Because the propagation medium of space laser communication is atmospheric channel,the signal quality will be affected by atmospheric turbulence effect and scattering.In order to cope with various influencing factors of the atmospheric channel,channel estimation and adaptive control technology can be used to improve the performance of the system under the premise of ensuring the quality of communication.This paper is mainly based on the satellite space laser communication scene.In order to solve the attenuation caused by the atmospheric channel,the channel estimation technology based on neural network and the adaptive modulation and coding technology based on artificial intelligence are mainly studied.The main research work and innovations of this paper are as follows:1.The atmospheric turbulence effect is modeled,and the transmission loss models such as turbulent fading,absorption and scattering of laser atmospheric channel are designed.Through OptiSystem simulation software,a satellite communication laser channel simulation link with multiple modulation formats is built,and the signal quality under different conditions is compared,which provides support for subsequent channel optimization research.2.Aiming at the problem that the channel estimation technology in adaptive modulation technology is not accurate enough,a back propagation(BP)neural network channel estimation technology based on ant colony optimization is proposed.The mean squared error(MSE)and signal-tonoise ratio(SNR)are used as the reference criteria,and their performance is compared by simulation.The results show that the proposed estimation technology can improve the accuracy of channel estimation,reduce the mean square error of estimation,and effectively improve the performance of channel estimation.3.Aiming at the large error of the traditional adaptive coded modulation strategy,a Q-learning adaptive coded modulation strategy based on Markov model is proposed.The channel state information and threshold interval are transformed into a dynamic mapping relationship,and the signal-to-noise ratio value of the laser link is continuously adjusted.The simulation results show that compared with the traditional fixed selection strategy,the channel throughput of the proposed scheme is closer to the ideal state,and the effective spectral efficiency of the channel is improved by about 20%,which is in line with the actual application.