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Cooperative beamforming method of large-scale MIMO system

A beamforming, large-scale technology that can be used in transmission systems, radio transmission systems, diversity/multi-antenna systems, etc.

Active Publication Date: 2020-05-19
INNER MONGOLIA UNIVERSITY
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Problems solved by technology

[0012] To sum up, in the existing literature, the performance of the traditional algorithm and the calculation delay are opposed, and the two cannot reach a high level at the same time. The algorithm based on deep learning mainly considers the spectral efficiency, or indirectly solves the beamforming matrix. Increased calculation delay

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  • Cooperative beamforming method of large-scale MIMO system
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[0080] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0081] In communication scenarios with large-scale antennas, beamforming design is crucial. The present invention considers that in a large-scale Multiple-Input and Multiple-Output (MIMO) heterogeneous network, under the constraints of the user's Quality of Service (QoS), a new system is proposed with the goal of maximizing system energy efficiency. A low-latency, energy-efficient cooperative beamforming algorithm.

[0082] Although the existing beamforming algorithms widely used in massive MIMO systems can achieve better system performance, the calculation delay increases significantly with the increase of the number of antennas, which is not suitable for massive MIMO systems. At the same time, in order to improve the practicability, although the...

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Abstract

The invention discloses a cooperative beamforming method for a large-scale MIMO system, and belongs to the field of wireless communication. The method comprises the steps: constructing a downlink large-scale MIMO heterogeneous network among a macro base station, a small base station and a user; considering the circuit power consumption of the base station, researching a system energy efficiency optimization problem satisfying QoS and antenna transmitting power constraints, and fully mining characteristics of a neural network; through the satisfactory performance of deep learning in regressiveproblems, fitting an optimal beamforming solution by extracting channel gain matrix characteristics; performing offline training by utilizing the neural network, and transferring a part of calculationto an offline part. Only a small amount of linear and nonlinear calculation is needed when the trained neural network is applied to solve, and the time delay is greatly reduced while the energy efficiency of the system is improved.

Description

technical field [0001] The invention belongs to the field of wireless communication, in particular to a cooperative beamforming method of a massive MIMO system. Background technique [0002] With the rapid increase of wireless communication users' data volume, the next generation mobile network puts forward higher requirements on system capacity and transmission rate. The spatial dimension is the source of improving the performance of wireless communication systems, so theoretical research and practical applications are carried out along the direction of expanding the spatial dimension. Professor Thomas L.Marzetta of Bell Labs proposed that a system composed of a large-scale antenna array can lay the foundation for the further development of the spatial dimension, and greatly improve the spectral efficiency of the system at the base station, creating a large-scale beamforming technology. First of its kind. American researchers predict that in 2020, the carbon emissions of ...

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Application Information

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IPC IPC(8): H04B7/0456H04B7/06H04B7/08
CPCH04B7/0456H04B7/0617H04B7/086Y02D30/70
Inventor 张颖慧张彪那顺乌力吉刘洋
Owner INNER MONGOLIA UNIVERSITY
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