Research On Reliable Terahertz Communication Technology Based On Multi-Connection

Virtual reality(VR)can provide immersive experience for users,attracting public attention and having a wide range of application scenarios in the future.To ensure the quality of experience(QoE),VR service has a large amount of data,as well as high requirements on communication rate and latency.Terahertz,with its abundant spectrum resources,is considered a key technology for the sixth generation of mobile communications and expected to meet the transmission needs of VR services in the future.However,terahertz signals have problems such as large path loss and penetration loss,and serious absorption by atmospheric molecules.Therefore,the transmission distance of terahertz signal is short,and the signal suffers from blockage easily,as a result,the application of terahertz signal is severely limited.However,in the multi-connection mode,a user device connects to multiple base stations and selects the best communication services based on the designed algorithm,which can improve the reliability of communication effectively.In this thesis,the research of terahertz communication technology based on multiconnection is carried out below:firstly,the communication performance of terahertz is analyzed based on hybrid blockage in multi-connection mode,and on this basis,a reliable multi-connection transmission scheme is designed considering the characteristics of VR services.The main work and innovations of this thesis are as follows:1.Hybrid blockage-based Performance analysis of multi-connection on terahertz communication system.In this part,a three-dimension Terahertz channel model is first established,by utilizing stochastic geometry,the performance of the multi-connection scheme is analyzed based on communication performance indicators such as link connectivity probability,blockage duration,and system throughput,considering dynamic blockage,static blockage,and self-blockage coexisting scenarios of Terahertz base stations.The related analysis is verified by Monte Carlo simulation.Results show that the multi-connection scheme can improve the effectiveness and reliability of Terahertz communications.2.Deep Reinforcement Learning(DRL)-based fast field of view rendering and transmission algorithm for terahertz-based VR system.In this part,recurrent Neural Network is used to predict the real-time field of view requests for VR users,and the field of view rendering task is completed at the base station.Then,based on the correlation between the user’s location and field of view request,a DRL strategy is used to achieve the best pairing between the base station responsible for downlink transmission and the VR user.Simulation results show that compared to directly selecting the nearest base station for field of view rendering and downlink transmission,the proposed view prediction and rendering scheme and DRL algorithm significantly improve the user’s quality of experience and reduce interaction delay.The research results in this thesis will provide a theoretical basis and technical support for the practical deployment of multi-connection-based terahertz communication system.