Multi-frequency Millimeter Wave Channel Measurements And Modeling For 5G Wireless Communication Systems

With the rapid developments of mobile Internet and Internet-of-things(IoT),mobile data services have grown explosively and enormous end users have connected to the mobile network.Compared with the fourth generation(4G)wireless communication systems,the capacity of the fifth generation(5G)wireless communication systems should have an increase of 1000 times.To realize it,many new technologies have been proposed to improve the performance of 5G wireless communication systems,among which millimeter wave(mmWave),massive multiple-input multiple-output(MMO),and ultra-dense network(UDN)have been the big three key technologies.Mm Wave has drawn many attentions and researches due to its huge communication bandwidths.Its application scenarios include cellular network,indoor hotspot,wireless backhaul and fronthaul,device-to-device(D2D),vehicular networks,etc.Meanwhile,mm Wave channel has some different propagation characteristics due to its high frequency,such as the high path loss,high penetration loss,effect of oxygen/water/vegetation attenuation,high directivity,human blockage,and multipath sparsity.Because its wavelength is short,the antenna form factor is small,the size of antenna array can be small and mm Wave can be complementary combined with massive MIMO to make full use of their advantages and largely improve the system performance.All these new channel propagation characteristics will bring great challenges to the applications of mmWave.Channel measurements and modeling are prerequisite for evaluation of wireless communication system performance.To realize and evaluate 5G mmWave communication systems,various mmWave channel measurements should be conducted and corresponding channel models should be proposed.This thesis gives a brief introduction of the developments of 5G wireless communication systems.Moreover,a comprehensive summary of mmWave frequency allocations,channel propagation characteristics,channel measurement methods,channel sounders,channel parameter estimation algorithms,channel modeling approaches,and standardized channel models is given.Extensive multi-frequency multi-scenario mmWave channel measurement campaigns are conducted and channel measurement data base is built.Various mmWave channel models are proposed.The main works and novelties are below:(1)60 GHz indoor channel measurements and modeling:A mm Wave channel measurement system is built and extended based on a vector network analyzer(VNA).The 60 GHz channel measurements are conducted in an indoor environment.The rotate directional antenna(RDA)and uniform virtual array(UVA)measurement methods are proved to be consistent.The effects of different antenna configurations on channel propagation characteristics are revealed.The space-alternating generalized expectation-maximization(SAGE)data post-processing algorithm is applied to extract multipath component(MPC)parameters.The ray tracing model and the SV model are developed.(2)Multi-frequency mmWave massive MIMO channel measurements and modeling:MmWave massive MIMO channel measurements are conducted in an indoor environment at 11,16,28,and 38 GHz bands for the first time and channel measurement data base is built.The SAGE algorithm is used to extract MPC parameters of the sub-array measurement data and the variations of MPC parameters over the array are studied.Channel propagation characteristics of different mmWave bands are compared.Massive MIMO properties such as near field spherical wavefront,cluster birth-death,and non-stationary properties at mmWave bands are validated.The propagation graph model and geometry based stochastic model(GBSM)are proposed.(3)A mmWave MIMO three dimensional(3D)wideband GBSM:A novel mmWave MIMO 3D wideband GBSM is proposed.Clusters are generated by a homogeneous Poisson point process(PPP)in 3D space.Scatterers are distributed in the two spheres at transmitter(Tx)and receiver(Rx)sides and corresponded to rays.The two spheres are used to model the MPC clustering property in delay and angular domains.The large-scale path loss model and line-of-sight(LOS)probability model are both considered.The accuracy of the proposed model is verified by comparing with mmWave channel measurement results.(4)A big data and machine learning(ML)enabled wireless channel model:A novel big data and ML enabled wireless channel modeling and statistical properties prediction method is proposed.The feed-forward neural network(FNN)and radial basis function neural network(RBF-NN)are both applied to predict channel statistical properties such as received power,delay spread(DS),and angle spreads(ASs).The performance of the proposed method is validated by training and testing of datasets collected from both real channel measurements and GBSM simulations.In summary,this thesis has done many works on mmWave channel sounders,channel measurements,parameter estimations,and channel modeling.Extensive multi-frequency multi-scenario mmWave channel measurements have been conducted.Various mmWave channel models have been proposed and verified by channel measurements.These works can have an important guidance significance for the realization of 5G mmWave wireless communication systems.