Method for selecting codebooks based on deep learning under large scale MIMO

Abstract

The invention relates to a method for selecting codebooks based on deep learning under large scale MIMO(Multiple-Input Multiple-Output) and belongs to the technical field of wireless communication. The method comprises following steps: acquiring pilot frequency information of a test zone to establish a pilot frequency training sequence and further obtaining a pilot frequency training sample; performing neural network iteration learning to the pilot frequency sample to obtain a final network weight value; selecting optical code words from a complete codebook according to the signal channel output by the neural network after learning. performing signal channel information matching to an unknown zone and the test zone to obtain a wireless signal channel thereof, and further obtaining code words corresponding to the wireless signal channel. By means of the method, wireless signal model and codebook query can be effectively, accurately and quickly established to avoid signal channel estimation of unknown zones and greatly reduce the complexity of unknown zone signal channel codebook selection.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and relates to a codebook selection method based on deep learning under massive MIMO (Multiple-Input Multiple-Output, multiple-input multiple-output). Background technique [0002] Any communication system, the channel is an essential component. The wireless channel is a typical "variable parameter channel". The characteristics of the wireless channel are closely related to the propagation environment, such as: terrain, surface features, climate characteristics, electromagnetic interference, communication object moving speed and frequency band used. The communication capability and quality of service (Quality of Service, QoS) of the wireless communication system are closely related to the performance of the wireless channel. Therefore, in order to transmit useful information with high quality and large capacity as possible on limited spectrum resources, it is necessary to have a g...

AI Technical Summary

Problems solved by technology

However, the former generally uses exhaustive search to find the optimal codeword, such as random search, alternate prediction, and Lloyd's iterative algorithm. The computational burden of these algorithms will increase sharply with the increase in the number of transmitting antennas.

While DFT systematically provides high chordal distances between precoding vectors, the average bit error rate is easily affected when transmit antennas suffer from high spatial correlation

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