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In this paper, based on the traditional LCMV beamformer and sub-array space partial adaptive array, a novel dimensionality reduction method is proposed. Firstly, the large-scale array is divided into several groups of sub-arrays according to a certain rule of sub-array division, and each group of sub-arrays uses the same weight. In the process of weight optimization, each time only a part of the weight vector is updated, the system search obtains the optimal weight through multiple iterations, which avoids the inversion of the full-dimensional correlation matrix. The experimental results show that compared with the traditional method, this method can obtain higher signal to interference and noise ratio and reduce the dimensionality of the inversion matrix in large-scale array beamforming, which reduces the computational complexity and hardware cost to a certain extent.

The new multiple access technology plays a very important role in 5G mobile communication system. In this article, a new non-orthogonal complex space division multiple(CSDM) technique is proposed and combined with traditional multiple input multiple output(MIMO) system to form CSDM-MIMO system. The CSDM-MIMO system can transmit multiple user data on one antenna at the same time and same frequency, which improves the data transmission rate and system capacity. The system special virtual channel is estimated by least squares(LS) algorithm and minimum mean square error(MMSE) algorithm respectively. At the same time, the optimal weight of the system is searched by the bit error rate(BER) fed back by the receiver and artificial fish swarm algorithm(AFSA).