Research on channel modeling of free space optical communication systems in time-varying environments based on machine learning
In time-varying environments,traditional models only remove some communication crosstalk and have high transmission losses.Therefore,a machine learning channel modeling method for free space optical communication systems in time-varying environments is proposed.The histogram statistical method is used to calculate the peak values of the dataset,select the shortest communication path,obtain the optimal channel parameters through genetic algo-rithm,calculate the communication impedance based on the optimal parameters through machine learning,obtain ca-pacitance and conductivity values,adjust the weights to remove communication crosstalk,convert the antenna domain into beam domain based on the channel size characteristics,and build a free space optical communication channel in a time-varying environment.The simulation experimental results show that the average transmission loss of the model in this paper reaches 148 dB,which is relatively low and has high application value.
machine learningtime-varying environmentfree space optical communicationfree space optical communicationtransmission loss
NETL
NSTL
万方数据
