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Large-scale MIMO system detection model construction method

A detection model and construction method technology, applied in transmission systems, radio transmission systems, transmission monitoring and other directions, can solve problems such as difficulty in massive MIMO detection, and achieve the effects of simple structure, low complexity, high detection performance, and few training parameters.

Active Publication Date: 2021-01-12
HARBIN ENG UNIV
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Problems solved by technology

However, the design of DetNet and ScNet networks is only for BPSK modulation scenarios, not suitable for high-order modulation communication scenarios, making it difficult to use deep learning for large-scale MIMO detection of high-order modulation

Method used

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  • Large-scale MIMO system detection model construction method
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  • Large-scale MIMO system detection model construction method

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Embodiment Construction

[0040] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0041] The present invention designs a deep learning-based ImNet network for large-scale MIMO systems with high-order modulation scenarios. The network combines the iterative method with deep learning to construct a fully connected network structure, and designs a sigSum activation function to Suitable for communication scenarios with high-order modulation.

[0042] The technical scheme of the present invention is specifically:

[0043] Step 1: Use iterative method combined with deep learning to approximate the target signal, divide the detection model into two modules, linear and nonlinear, and construct a layer-by-layer iterative network structure;

[0044] Step 2: The linear module combines the linear combination of known information to linearly estimate the transmitted signal x, and introduces trainable variables and weight matrices in ...

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Abstract

The invention discloses a construction method of a large-scale MIMO system detection model, and the model is formed by iterating K layers of same networks, each layer of network is divided into a linear module and a nonlinear module, the linear modules are combined with a linear combination of known information, training parameters are added, and linear estimation is carried out on a sending signal x. And the nonlinear module performs multi-segment mapping on the linear estimation value to obtain a nonlinear estimation value, and in addition, a residual structure with a variable residual coefficient is added into each layer of network. The constructed detection model is simple in network structure, and has the characteristics of strong network adaptive capacity, high convergence speed andlow complexity.

Description

technical field [0001] The invention relates to a method for building a detection model of a massive MIMO system, in particular to a method for building a detection model for a large-scale MIMO system based on deep learning, and belongs to the technical field of wireless communication. Background technique [0002] In recent years, with the explosive growth of the number of mobile terminals such as smart phones, terminal applications and mobile services have become increasingly diversified, the traditional small-scale MIMO system has been unable to meet the requirements of various mobile services for communication rate and channel capacity, so MIMO Technology is also gradually developing in the direction of large-scale. Compared with the traditional MIMO system, the massive MIMO system expands the number of equipment antennas from the original maximum of eight to dozens or even hundreds, further improving the performance of the communication system. [0003] Deep learning h...

Claims

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Application Information

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IPC IPC(8): H04B7/0413H04B17/391
CPCH04B7/0413H04B17/391
Inventor 禹永植王建明郭立民张春红陈艳
Owner HARBIN ENG UNIV
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