Research On Trajectory Prediction Algorithm Of High-altitude Communication Broadband Signal Source

High-altitude communication broadband signal source is considered as one of the effective solutions to expand communication coverage in the fifth generation mobile communication technology.However,due to the effects of high-altitude airflow,pressure,and wind,the High Altitude Platform(HAP)is usually in an unstable state,It is impossible for gateways and HAPs on the ground to achieve accurate beamforming,resulting in unnecessary capacity loss in HAP communication systems.To solve the above problem,this paper proposes a broadband signal source trajectory prediction algorithm based on DOA estimation algorithm and deep learning.The state of broadband signal sources in high-altitude communication at the next moment can be accurately predicted by DOA estimation and deep learning.The main work of this paper is as follows:Firstly,this paper introduces the development of wireless communication network,high-altitude platform communication system,broadband signal source arrival angle parameter estimation,machine learning algorithm and deep learning algorithm.Aiming at the problem of wideband signal source trajectory prediction algorithm in high-altitude communication,this paper proposes a method to estimate the trajectory data through the parameters of the two-dimensional arrival angle of the HAP,achieving to predict the next trajectory position.Then,this paper introduces the model structure of LSTM and attention network in deep learning in detail,and proposes a wideband signal source trajectory prediction method based on deep learning model.In this method,the trajectory information of the wideband signal source is obtained by DOA estimation algorithm of the panel antenna array.Next,a series of data preprocessing methods are used to ensure the validity and stability of the trajectory information data.Finally,LSTM and attention model models are used to build simulation prediction models in different communication scenarios,so that the state information of the broadband signal source at the next moment can be accurately predicted.Finally,this article shows the simulation results of LSTM and attention model in two different smart city communication scenarios.Comparing the results of different methods in the two different smart city communication scenarios ensures the most accurate prediction model.The results show that the proposed trajectory prediction algorithm for broadband signal sources in this paper has higher accuracy,which enables gateways and HAPs to achieve accurate beamforming,reduces unnecessary capacity loss,and improves the reliability of 5G HAP communication systems.