Research And Analysis Of A New Channel Model In Wireless Communication System

In recent years,the continuous growth of demand for communication services has promoted the rapid development of communication systems.As the cornerstone of the design and optimization of communication systems,wireless channels undoubtedly play a crucial role.Today,the research of the fifth generation(5G)communications technology is expected to be fully commercialized in 2020.The introduction of multiple input multiple output(MIMO)technology and large-scale MIMO technology can greatly improve the efficiency and capacity of the communication system.The advent of the era of big data,the rapid development of the Internet of things and the interconnection of traffic vehicles are heralding yet another peak in the communications era.Based on the traditional space statistical channel modeling,this paper focuses on the current hot spots and trends and studies the MIMO channel model with multi-antenna array.In this paper,the author proposes a novel cluster-based geometrical dynamic stochastic model for MIMO communication environments.The channel model assumes base station(BS)has an adaptive learning ability and data processing capabilities.In this model,the BS first parses the continuously received data to obtain a usable data set.And the initial data set which reflects the scatterer information in the wireless environment will be preprocessed in advance.Subsequently,treating the data as input,scatterers can be clustered into different clusters based on density based spatial clustering of applications with noise(DBSCAN)algorithm.Finally,based on the clustering results,a unique elliptical channel model for each scattering cluster will be constructed.Based on this,the author derives the closed-form expression for marginal probability density function(PDF)of the angle of arrival(AoA)and the expression of the space-time cross-correlation function between different scattering clusters.At the same time,Close agreement is achieved between the results obtained in this study and previously reported results,thereby validating the generalization of the proposed channel model,and further verifies the feasibility of integrating the machine learning theory into the traditional channel model.For channel modeling based on spatial statistics,the impact of vertical angle on system performance cannot be neglected.Based on this,the author proposes a three-dimensional(3D)semi-ellipsoid scattering channel model in vehicle-to-vehicle(V2V)radio propagation environment,in which a directional large-scale antenna array are both employed at the mobile transmitter(MT)and the mobile receiver(MR).The relative motion bet-ween MT and MR results in a time-varying geometric statistics.The channel impulse repose between any antenna of MT and MR are derived in this paper.Besides,the marginal PDFs of the AoA statistics at the MT and MR in the horizontal and vertical planes are also derived.The results show that the proposed 3D model fits the previously two-dimensional and 3D channel models very well,which demonstrate that the proposed model is practical to characterize real V2V channels.