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SVD (Singular Value Decomposition) method and SVD device of MIMO (Multiple Input Multiple Output) pre-coding technology

A singular value decomposition and precoding technology, applied in the field of singular value decomposition methods and devices of MIMO precoding technology, can solve problems such as high computational complexity, and achieve the effects of low computational complexity, high throughput, and reduced iteration times

Inactive Publication Date: 2014-01-08
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, in the process of implementation, a large number of matrix multiplications, vector modulo operations and division operations are required, so it has high computational complexity.

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  • SVD (Singular Value Decomposition) method and SVD device of MIMO (Multiple Input Multiple Output) pre-coding technology
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  • SVD (Singular Value Decomposition) method and SVD device of MIMO (Multiple Input Multiple Output) pre-coding technology

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Embodiment Construction

[0047] The implementation of the present invention is described below through specific examples and in conjunction with the accompanying drawings, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific examples, and various modifications and changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention.

[0048] figure 1 It is a flowchart of steps of a singular value decomposition method of a MIMO precoding technology in the present invention. like figure 1 Shown, the singular value decomposition method of a kind of MIMO precoding technology of the present invention comprises the following steps:

[0049] Step 101, converting the channel matrix H into a Hermitian matrix A=H H *H, matrix A...

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Abstract

The invention discloses an SVD (Singular Value Decomposition) method and an SVD device of an MIMO (Multiple Input Multiple Output) pre-coding technology. The SVD method comprises the following steps of converting a channel matrix H into a Hermitian matrix A (A = HH * H), and converting a question for calculating SVD of the channel matrix H into a question for calculating EVD (Eigen Value Decomposition) of the Hermitian matrix A, wherein a diagonalizable matrix of the Hermitian matrix A is just a calculated pre-coding matrix; carrying out EVD iteration on the Hermitian matrix A and calculating a diagonalizable matrix V of the Hermitian matrix A. According to the method and the device, disclosed by the invention, a pre-coding method with a lower calculation complexity can be realized on the premise that the error rate performance of a communication system is ensured, and a pre-coding circuit with high throughput rate and low hardware complexity can be realized at the same time.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, in particular to a singular value decomposition method and device of MIMO precoding technology. Background technique [0002] With the rapid development of science and technology, modern communication technology is developing in the direction of digitization, high speed, and low power consumption. With the needs of multimedia applications, traditional wireless communication technologies such as Bluetooth, wireless local area network (WLAN) and ultra-wideband (UWB) can no longer meet the needs of users for high-speed wireless data transmission rates. The data transmission rate comparable to that of the multimedia interface (HDMI), so the high-speed wireless communication system that can realize the transmission rate of Gigabit / s or even several Gigabit / s has become a new hot spot in the field of wireless communication. [0003] Multiple-input multiple-output (MIMO) technolo...

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Application Information

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IPC IPC(8): H04L1/06H04B7/06
Inventor 龚小章贺光辉
Owner SHANGHAI JIAO TONG UNIV
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