Millimeter wave MIMO antenna and hybrid beam forming optimization method and system

Abstract

The invention provides a millimeter wave MIMO antenna and hybrid beam forming optimization method and system. The method comprises the following steps: acquiring a training sample set; constructing a deep learning neural network model; initializing related parameters of the deep learning neural network model; training the deep learning neural network model by using the training sample set, and storing the trained deep learning neural network model; and inputting set network input data into the stored deep learning neural network model for prediction, and obtaining an optimal antenna sub-array, a transmitting end optimal simulation precoder matrix and a receiving end optimal simulation combiner matrix when the spectral efficiency is maximum. The antenna selection problem and the hybrid beam forming problem are jointly optimized by using the deep learning neural network, the performance and the algorithm complexity can be considered at the same time, the time delay can be reduced on the premise of ensuring the performance, and the millimeter wave large-scale MIMO system can provide real-time service.

Description

technical field [0001] The present application relates to the technical field of mobile communication, and in particular to a millimeter-wave MIMO antenna and hybrid beamforming optimization method and system. Background technique [0002] In recent years, millimeter-wave massive MIMO wireless transmission technology can expand and utilize new spectrum resources, deeply mine spatial dimension wireless resources, and greatly increase wireless transmission rates. It is one of the most potential research directions to support future broadband mobile communications. [0003] As the number of massive MIMO antennas increases, the complexity of encoding and decoding algorithms in multi-antenna communication systems will also increase, which is not conducive to practical applications. Reducing radio frequency links through antenna selection technology can reduce the complexity of encoding and decoding algorithms. However, the traditional antenna selection technology is difficult to ...

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Problems solved by technology

[0003] As the number of massive MIMO antennas increases, the complexity of encoding and decoding algorithms in multi-antenna communication systems will also increase, which is not conducive to practical applications. Reducing radio frequency links through antenna selection technology can reduce the complexity of encoding and decoding algorithms. However, the traditional antenna selection technology is difficult to solve the problem of obtaining the optimal antenna subset while reducing the complexity of the algorithm; at the same time, in the research of millimeter-wave massive MIMO systems, the hybrid beamforming technology c

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