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A low-complexity hybrid precoding method was proposed to design the hybrid precoding for mmWave massive MIMO system.Firstly,an initial radio frequency(RF)precoding matrix was constructed based on the singular value decomposition.Then an updated RF matrix was constructed by placing the vector which was constructed by the biggest left singular vectors of the residual matrix onto the last column of the initial RF matrix.By multiple iterations,the resultant RF precoding matrix can be obtained and the digital precoding matrix was designed based on the least square criterion.Theoretical analysis and simulation results show that the proposed algorithm greatly outperforms the hybrid precoding method based on orthogonal matching pursuit(OMP)algorithm with much reduced computational complexity.Additionally,the proposed hybrid precoding method has almost the same performance as the full digital precoding method when the number of data stream is relatively less.

To improve the imaging quality in the minimum variance method of lowcomplexity， an improved low-complexity amplitude and phase estimation beamforming algorithm was proposed. The adaptive weighted value was calculated by extracting the effective rows of the covariance matrix， where the selection of the effective number of rows was determined by a more accurate Gaussian phase coherence coefficient， which was then used to modify the weighting vector in order to reduce the complexity and ensure the quality of the imaging at the same time. Through experimental verification， the improved algorithm was compared with the original algorithm and another beamspace method to reduce the complexity， which fully proves the superiority of the improved algorithm in reducing the complexity and improving the imaging quality. [ABSTRACT FROM AUTHOR]