Deep learning-based MIMO decoding method and apparatus, and storage medium

A decoding method and deep learning technology, applied to devices and storage media, in the field of MIMO decoding methods based on deep learning, can solve problems such as low decoding performance, achieve high decoding accuracy, ensure overall performance, and improve the effect of approximation

Active Publication Date: 2019-06-21
深圳市宝链人工智能科技有限公司
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the embodiments of the present invention is to provide a deep learning-based MIMO decoding method, device, and storage medium, which can at least solve the problem of approximate and sub-par MIMO decoding using linear MIMO decoding schemes and iterative MIMO decoding schemes in related technologies. Excellent, low decoding performance issues

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  • Deep learning-based MIMO decoding method and apparatus, and storage medium
  • Deep learning-based MIMO decoding method and apparatus, and storage medium
  • Deep learning-based MIMO decoding method and apparatus, and storage medium

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no. 1 example

[0031] In order to solve the technical problems that linear MIMO decoding schemes and iterative MIMO decoding schemes are used for MIMO decoding in related technologies, the results are approximate and suboptimal, and the decoding performance is low. This embodiment proposes a MIMO decoding method based on deep learning. ,Such as figure 2 Shown is a schematic flow chart of the MIMO decoding method based on deep learning provided in this embodiment. The MIMO decoding method based on deep learning proposed in this embodiment includes the following steps:

[0032] Step 201, constructing a training data set for MIMO decoding, where the training data set includes a plurality of training data.

[0033] Specifically, the neural network is trained under the framework of supervised learning, so in this embodiment it is necessary to construct a training data set, so as to train the neural network based on multiple training data in the training data set.

[0034] In an optional impleme...

no. 2 example

[0056] This embodiment shows a MIMO decoding device based on deep learning, such as Figure 4 Shown is a schematic structural diagram of the MIMO decoding device provided in this embodiment, in order to solve the problem that linear MIMO decoding schemes and iterative MIMO decoding schemes are used for MIMO decoding in the prior art, the results are approximate and suboptimal, and the decoding performance is low Problem, the MIMO decoding device in this embodiment includes:

[0057] The training set construction module 401 is used to construct a training data set for MIMO decoding, and the training data set includes a plurality of training data;

[0058] The model training module 402 is used to train the neural network based on the training data set to obtain a trained neural network model;

[0059] The decoding module 403 is configured to input the MIMO signal to be decoded to the neural network model for MIMO decoding when receiving the MIMO signal to be decoded, and then ...

no. 3 example

[0074] This embodiment provides an electronic device, see Figure 5 As shown, it includes a processor 501, a memory 502 and a communication bus 503, wherein: the communication bus 503 is used to realize connection and communication between the processor 501 and the memory 502; the processor 501 is used to execute one or more programs stored in the memory 502 A computer program to implement at least one step in the MIMO decoding method based on deep learning in the first embodiment above.

[0075] The present embodiment also provides a computer-readable storage medium, which includes information implemented in any method or technology for storing information, such as computer-readable instructions, data structures, computer program modules, or other data. volatile or nonvolatile, removable or non-removable media. Computer-readable storage media include but are not limited to RAM (Random Access Memory, random access memory), ROM (Read-Only Memory, read-only memory), EEPROM (Ele...

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Abstract

The embodiment of the invention discloses an MIMO decoding method and device based on deep learning and a storage medium, and the method comprises the steps: building a training data set of MIMO decoding, and enabling the training data set to comprise a plurality of pieces of training data; Training the neural network based on the training data set to obtain a trained neural network model; And when a to-be-decoded MIMO signal is received, inputting the to-be-decoded MIMO signal into the neural network model for MIMO decoding, and then obtaining an MIMO decoding result output by the neural network model. Implementation by the invention, A neural network model used for joint MIMO detection and channel decoding is designed based on deep learning. According to the method, MIMO detection and channel decoding are taken as a joint decoding process, the approximation of an output result of a neural network model is improved through training, the overall performance of MIMO decoding is ensured,and the method has higher decoding accuracy and faster decoding speed.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a deep learning-based MIMO decoding method, device and storage medium. Background technique [0002] Multi-antenna technology, also known as Multiple-Input Multiple-Output (MIMO, Multiple-Input Multiple-Output), is one of the most important technologies in advanced wireless communication systems. It has been proved in theory that MIMO can increase the number of transmitting and receiving antennas. while increasing its spectral efficiency linearly. In practice, MIMO has been incorporated into many wireless communication standards, such as 802.11n / ac and LTE 4G. [0003] In order to achieve close to channel capacity, advanced channel coding schemes such as low density check codes and polar codes have been proposed in the related art. These channel codes can protect data streams from channel fading, interference and noise. When performing MIMO decoding on the channe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L1/00H04B7/0413G06N3/04
Inventor 王滔滔张立豪张胜利汪炜岳力
Owner 深圳市宝链人工智能科技有限公司
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