Research On Channel Estimation And Beam Alignment Of Millimeter Wave Massive MIMO

With the development of the demand for future communication,the increase of highrate communication scenarios,and the shortage of frequency resources in the lowfrequency,millimeter wave communication technology,as it has more spectrum resources,larger communication bandwidth,and can effectively utilize the resources in the spatial domain,has attracted a lot of attenatiaon from many aspectes.Therefore,it has become one of the important technologies of 5G communication.In this dissertation,the author firstly study the millimeter wave communicaton channel characteristic,based on the previous research of the millimeter wave channel measurements,the different millimeter wave multiple input multiple output(MIMO)structure,the sparsity of millimeter wave channels.Then,for the three core problems in millimeter wave MIMO,namely antenna aperture,mobility and wideband,study the pilot overhead,wideband channel estimation,mobility,and beam alignment problems.First,this dissertation summarize existing literature study of millimeter wave channel characteristic,then make the channel measurement of actual special scenes,and forms the analysis results of outdoor to indoor(O2I)channel.Then,the millimeter wave channel beamspace is studied combined with the sparsity.The grid less problem is discussed and the relevant simulations are done to verify the existence of this phenomenon.Besides,the three core mathematical tools of compressive sensing(CS),tensor decomposition,and sparse coding techniques are discussed.Then,based on the millimeter wave massive MIMO architecture,problems of parameter extraction in wideband channels are studied,and the beam squit problem due to the space-wideband effect is further studied.On the one hand,aiming at the traditional millimeter wave wideband channel model,a channel estimation scheme based on dimension superposition is proposed.For the final simulation results,this method can effectively extract wideband channel parameters and avoid the lattice mismatching phenomenon.On the other hand,since the bandwidth is wide enough,antenna aperture is large enough,the new effect under the condition of channel model is studied.Then,a low complexity channel estimation algorithm is proposed,which improves the estimation efficiency and reduces the complexity of the system.Then,in the fourth chapter,some time-varying channel estimation algorithms are proposed for the future high speed scenarios such as the internet of vehicles,high-speed mobile wearables and high-speed trains.First,the difference between millimeter wave time-varying channel and low-frequency time-varying channel is analyzed,and the millimeter wave time-varying channel model is determined based on the measurement results.Second,a time-varying channel estimation method based on tensor decomposition is proposed by making full use of the time dimension information.Finally,based on the block sparsity and low rank characteristic,a joint estimation algorithm is proposed by utilizing the block orthogonal matching pursuit(BOMP)and ANDECOMP/PARAFAC(CP)methods.At the same time,the cramer-rao lower bound(CRLB)of the parameters of the time-varying channel is derivated.Moreover,in order to study the performance of millimeter-wave communication in broadband time-varying channel,the performance of the latest Orthogonal Time Frequency Space(OTFS)in millimeter-wave Frequency band is simulated,and the possible channel estimation scheme of MIMO-OTFS system is analyzed.Finally,in order to reduce the complexity of millimeter channel estimation algorithms,the beam alignment methods are studied.First,the model of hierarchical sparse coding matrix is established,and the success probability of peeling off algorithm based on the basic model of message passing(MP)is deduced.Then,an uplink multiuser beam alignment algorithm is proposed,and the simulation results demonstrate its improved performance.Based on the beam alignement framework,a millimeter-wave beam alignment algorithm is proposed for the time-varying channel,which can extract the doppler shift of the maximum path.Compared with the conventional algorithm based on compressed sensing,the algorithm reduces the complexity and has strong robustness.