| The aspiration for higher data rates and more reliable communications has led a lot of engineers and researchers in the telecommunications industry to develop new technologies.This requires big changes to existing infrastructure and user equipment.One of the proposed technologies for the fifth generation(5G)cellular communication systems are massive Multiple-Input Multiple-Output systems(MIMO).Massive MIMO can improve the performance by providing large spatial multiplexing and diversity gains and is considered as one of the technologies that allow to increase the speed of data transmission for future communication systems.Nowadays especially paid attention on large-scale antenna system(LSAS)and millimeter wave(mmWave)communication.LSAS could obtain beamforming gain from an antenna array,which greatly improves spectral efficiency.In addition,there are a large number of unallocated bandwidth resources in the millimeter wave,which can significantly expand the system bandwidth.Therefore,LSAS and mmWave communication are likely to become important technologies in 5G systems for solving communication overload.With full digital LSAS beamforming that can optimally perform beamforming,the system antenna number must match the number of radio frequency(RF)circuits so that each antenna element has a dedicated RF chain and baseband processing module,which results power consumption and high cost of equipment.Consequently,in practical solutions,a digital-to-analog hybrid beamforming structure(HBF)would be a good choice for the trade-off between performance and cost.The HBF architecture uses only a limited number of RF circuits,and the system complexity and equipment cost are reduced,and the performance loss is acceptable,which provides a trade-off between system performance and equipment complexity plus cost.In this thesis,firstly,we introduced the basic model and the response vector of antenna array,and then presented the channel model that commonly used in mmWave communication.In order to further state the principle and meaning of beamforming,we analyze conventional analog beamforming(ABF)algorithms based on beam steering,beam nulling and minimum variance distortionless response(MVDR),and digital beamforming(DBF)algorithms based on zeroforcing(ZF),minimum mean square error(MMSE),singular value decomposition(SVD),block diagonalization(BD)and codebook based.Secondly,several HBF algorithms for downlink transmission,i.e.beamspace MIMO,alternating HBF methods,phased-ZF HBF algorithm and two-stage HBF scheme based on codebook feedback,are studied.The performance of HBF algorithms is simulated and compared to analyze the existing problems and limitations of these conventional schemes.With the Hybrid beamforming architecture,we proposes an improved HBF scheme based on signal to leakage and noise ratio(SLNR)criterion.Also,due to the existing problem in FDD and TDD systems that perfect channel state information(CSI)cannot be obtained under HBF architecture,a HBF algorithm based on uplink training is proposed in this thesis,using the channel reciprocity existing in TDD systems.By uplink training,this algorithm could obtain the optimal joint beamforming matrix.Then we decomposed the optimal joint beamforming matrix into analog beamforming matrix and digital beamforming matrix.Based on designed analog beamforming algorithm,the best codebook vectors would be found in the codebook set,forming analog beamforming matrix.And digital beamforming matrix can be obtained directly in the form of leastsquare solution to complete the downlink hybrid beamforming algorithm design. |
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