| Satellite communication has the advantages of wide coverage,independent of geographic conditions and natural disasters,etc.It is an important trend of future technology development to combine with terrestrial network to form a wide area coverage communication system.Free Space Optical(FSO)communication has the characteristics of high data rate,high security,low power consumption,etc.which can meet the requirements of satellite communication system design for communication load and communication rate.However,FSO communication is susceptible to various external factors,so combining the advantages of Radio Frequency(RF)communication with FSO communication to form a FSO/RF hybrid link which can effectively improve the system reliability.Currently,the technologies of multi-station diversity,adaptive switching,coding modulation,channel equalization and estimation prediction for FSO/RF hybrid links have become hot topics in the field of laser-microwave heterogeneous networking for satellite communication.This paper models the switching problem of FSO/RF hybrid links for single/dual station satellite-ground communications based on a Finite-State Markov model,and analyzes the system performance numerically.A channel state prediction algorithm based on machine learning is proposed for an adaptive modulation technique applicable to FSO/RF hybrid links.The specific work is as follows:(1)According to the characteristics of the satellite-ground communication scenario and the influence of different meteorological parameters conditions,the channel fading of FSO link and RF link are selected as Gamma-Gamma distribution model and Ricean distribution model,respectively,as a way to compare and analyze the single/dual station FSO/RF hybrid link performance.Based on the finite state Markov model of FSO/RF hybrid link in single/double station scenario and its steady state probability solving method,the corresponding outage probability expressions are derived,and the closed expressions for the BER of the FSO/RF hybrid link are derived by Meijer G functions,and the BER and outage probability performance of the system is analyzed by numerical calculations.Numerical calculations show that both severe weather conditions and long-distance transmission degrade the link performance;the dual station FSO/RF hybrid link outperforms the single station one,and when the outage probability 10-6 and the link distance is 1km to 7km under rainy and foggy weather conditions,the dual ground station FSO/RF hybrid link achieves a gain of about 4dB-25dB compared to the single station system.(2)Based on the ideas of machine learning channel state prediction and link margin calculation,an adaptive switching modulation technique suitable for satellite ground FSO/RF hybrid links is proposed.Based on the BER expressions of FSO and RF link,the BER performance of different modulation methods under severe weather conditions is simulated and analyzed,and the switching threshold LMth of different modulation methods is obtained based on the set target BER Pe,obj.The current corresponding channel state is obtained from the actual weather data and the divided switching threshold.And the obtained weather data set and the channel state set are used to train the machine learning model.Moreover,the additional weather data are used to test the performance of the obtained model.(3)The proposed model is tested and analyzed with the observed weather dataset,and the performance of adaptive modulation and non-adaptive modulation,and the experimental statistical and theoretical results of FSO link adaptive modulation spectral efficiency in rainy days are compared and analyzed.The results show that the performance of adaptive modulation is significantly better than that of non-adaptive modulation,and the experimental statistical results of adaptive modulation are consistent with the theoretical results,and its modulation order and spectral efficiency decrease with the increase of rainfall rate. |
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