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Large-Scale MIMO Signal Detection Method Based on Jacobian Iteration

A signal detection, large-scale technology, applied in diversity/multi-antenna systems, space transmit diversity, electrical components, etc., can solve problems such as high computational complexity, achieve good iterative convergence, reduce computational complexity, and fast convergence rate Effect

Active Publication Date: 2020-10-09
JIANGNAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, as the number of antennas increases, the MMSE detection algorithm has a high-dimensional matrix inversion process, which has high computational complexity.

Method used

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  • Large-Scale MIMO Signal Detection Method Based on Jacobian Iteration
  • Large-Scale MIMO Signal Detection Method Based on Jacobian Iteration
  • Large-Scale MIMO Signal Detection Method Based on Jacobian Iteration

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Embodiment 1

[0041] This embodiment provides a Jacobian-based iterative massive MIMO signal detection method, the method comprising:

[0042] Step 1: Construct the minimum mean square error detection MMSE detection matrix A according to the channel response matrix H;

[0043] Step 2: Decompose the detection matrix A according to A=D+E, wherein D represents the diagonal matrix of the detection matrix A, and E represents the off-diagonal matrix of the detection matrix A;

[0044] Step 3: Use the gradient algorithm to provide the search direction for the Jacobian algorithm, and obtain a hybrid iterative process of the Jacobian and the gradient algorithm;

[0045] Step 4: Improve the hybrid iterative process in step 3 by using the overall correction acceleration method to obtain the correction coefficient of the iterative equation, and then obtain the correction solution;

[0046] Step 5: According to the matrices A, D, E, gradient algorithm and overall correction acceleration method, the impro...

Embodiment 2

[0049] This embodiment provides a Jacobian-based iterative massive MIMO signal detection method, the method comprising:

[0050] Step 1: Construct the minimum mean square error detection MMSE detection matrix A according to the channel response matrix H;

[0051] Step 2: Decompose the detection matrix A according to A=D+E, wherein D represents the diagonal matrix of the detection matrix A, and E represents the off-diagonal matrix of the detection matrix A;

[0052] Step 3: Use the gradient algorithm to provide the search direction for the Jacobian algorithm, and obtain a hybrid iterative process of the Jacobian and the gradient algorithm;

[0053] Step 4: Improve the hybrid iterative process in step 3 by using the overall correction acceleration method to obtain the correction coefficient of the iterative equation, and then obtain the correction solution;

[0054] Step 5: According to the matrices A, D, E, gradient algorithm and overall correction acceleration method, the imp...

Embodiment 3

[0085] This embodiment provides a Jacobian-based iterative massive MIMO signal detection method, the method comprising:

[0086] Step 1: Construct the minimum mean square error detection MMSE detection matrix A according to the channel response matrix H;

[0087] Step 2: Decompose the detection matrix A according to A=D+E, wherein D represents the diagonal matrix of the detection matrix A, and E represents the off-diagonal matrix of the detection matrix A;

[0088] Step 3: Use the gradient algorithm to provide the search direction for the Jacobian algorithm, and obtain a hybrid iterative process of the Jacobian and the gradient algorithm;

[0089] Step 4: Improve the hybrid iterative process in step 3 by using the overall correction acceleration method to obtain the correction coefficient of the iterative equation, and then obtain the correction solution;

[0090] Step 5: According to the matrices A, D, E, gradient algorithm and overall correction acceleration method, the imp...

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Abstract

The invention discloses a large-scale MIMO signal detection method based on Jacobi iteration, and belongs to the technical field of wireless communication. The method comprises the steps: converting amatrix inversion process into an iteration process of matrix multiplication and matrix addition, providing the search direction for a Jacobi algorithm through a gradient algorithm and an overall correction acceleration method, and determining a correction coefficient of an iteration equation. According to the invention, the method performs the estimation of a high-dimensional matrix inversion process through an improved Jacobi iteration method, and converts the matrix inversion process into the iteration process of matrix multiplication and matrix addition, thereby greatly reducing the computing complexity. The gradient algorithm and the overall correction acceleration method are used for providing the search directions for the Jacobi algorithm and determining the correction coefficient of the iteration equation, thereby enabling the iteration convergence to be better, and enabling the convergence speed to be higher.

Description

technical field [0001] The invention relates to a large-scale MIMO signal detection method based on Jacobian iteration, and belongs to the technical field of wireless communication. Background technique [0002] The large-scale MIMO (Large Scale-Multiple-Input Multiple-Output, LS-MIMO) system is one of the key technologies of the fifth generation mobile communication system. By configuring a large number of antennas at the base station and the user end, the channel capacity of the system can be significantly improved. Data transfer rate, spectral efficiency and communication quality. [0003] Due to the increase in the number of antennas, many high-performance methods suitable for traditional MIMO systems are no longer suitable for massive MIMO systems, and these methods often result in higher complexity. Therefore, how to reduce the complexity of the method while maintaining good performance has become an urgent problem to be solved. Traditional signal detection methods c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B7/0413H04B7/08
CPCH04B7/0413H04B7/0854
Inventor 李正权赵小青周成梁金鹏刘汉旭刘洋吴琼李宝龙
Owner JIANGNAN UNIV
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