Abstract
In the Tibetan Plateau, due to lack of raw experimental data sets and proper data analysis method, investigations on atmosphere laser communication channel (ALCC), especially under rainy condition, are rarely concerned by researchers. Neural network group and optimal weight initialization technology (OWIT) are adopted in the analysis process. Firstly, construct neural network group according to different season’s conditions. Secondly, utilize existed raw data sets of ALCC under rainy condition to choose matching initial weight sets with OWIT. Thirdly, train neural network group until expected requirement is met. Finally, load rain data sets from the Tibetan Plateau (Lhasa for example) on trained neural network group to achieve the ultimate channel quality of ALCC. Actual results show that spring rain has the best quality of ALCC, followed by winter rain, summer rain and autumn rain.
Highlights
The Tibetan Plateauɼalso known as Himalayan Plateau, is a vast plateau covering most of the Tibet Autonomous Region and Qinghai Province in western China
Free-space optical communication (FSO) is an optical communication technology which adopts light propagating in free space to transmit data
atmosphere laser communication channel (ALCC) is a channel adopted atmosphere as transmission medium, which is very vulnerable for bad weather condition, such as fog, rain etc. [1]
Summary
The Tibetan Plateau (called Qinghai-Tibet Plateau)ɼalso known as Himalayan Plateau, is a vast plateau covering most of the Tibet Autonomous Region and Qinghai Province in western China. FSO is a costeffective technique which has application prospects in the Tibetan Plateau. ALCC is a channel adopted atmosphere as transmission medium, which is very vulnerable for bad weather condition, such as fog, rain etc. 2. THE MAIN DIFFICULTIES IN ANALYZING ALCC UNDER RAINY CONDITION IN TIBETAN PLATEAU. Lack of direct raw experimental data sets is the main difficulty. To obtain direct raw experimental data sets, expensive measure equipments, professional technicians and other resources are fundamental conditions. Using the data sets above, how to achieve the quality of ALCC in Tibetan Plateau?. It is difficult to build direct mathematic model between available data sets and channel quality from Fig.
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