Theoretical Research On The Geometric Stochastic Channel Modeling For Industrial IoT

Industrial Internet of Things(IIoT)is the product of applying wireless communication technology to industrial smart manufacturing,and is one of the important application scenarios in the fifth generation(5G)and the sixth generation(6G)mobile communication systems.Channel modeling is the basis for communication system design and optimization.However,compared with other indoor scenarios,IIoT scenarios are characterized by large space,rich material types,large and densely distributed metal devices,resulting in more complex fading characteristics of IIoT channel.The complex channel characteristics bring great challenges for building accurate and effective IIoT channel models.There are still several channel properties that have not been fully considered in the existing models,such as frequency consistency,rich scatters,multi-mobility and random Doppler shifts.In view of the shortcomings of existing IIoT channel models,this paper deeply studies the characteristics of IIoT channel.Then,two geometry-based stochastic models(GBSM)for IIoT scenarios are established.The main work and innovations of this thesis as follows:(1)A GBSM with frequency-consistent for IIoT scenarios is proposed to solve the frequency consistency and non-stationary characteristics of IIoT channel.Firstly,the channel parameters of different frequency are initialized based on the theory of sum of sinusoids to study the frequency consistency of the channel.Then,the space-time-frequency non-stationary characteristics of IIoT channel are described by using the birth-death evolution process of the cluster on the space-time-frequency axis.Finally,the proposed model is validated by the variation trend of channel parameters on the frequency axis,the fitting results of the root-meansquare delay spread(RMS DS)and the matrix diagram of the visible cluster.(2)A general GBSM for IIoT scenarios is established by deeply studying the characteristics of IIoT channel,such as rich scatters,multi-mobility and random Doppler shifts.Firstly,a single-bounce mechanism is introduced to construct the path component of the strong specular reflection component caused by large metal devices,and the corresponding channel parameters are calculated based on geometric optics.Then,the characteristics of densely distributed in IIoT channels are studied,the generalized extreme value distribution and generalized Pareto distribution are used to parameterize the number of clusters and rays within a cluster for IIoT channel at millimeter-wave bands,respectively.In addition,considering the random Doppler offsets caused by the random or periodic swing of robots,smart vehicles and robotic arms in IIoT environment,the Gaussian distribution is used to correct the traditional Doppler shift model.Finally,this paper verifies the accuracy and reliability of the proposed model by deriving some channel statistical characteristics and simulations,such as power delay profile,RMS DS,inter-cluster delay and space-time-frequency correlation function.