Time-varying channel estimation method based on millimeter wave time-varying channel block sparsity and low rank

A time-varying channel, millimeter wave technology, applied in channel estimation, baseband system components, radio transmission systems, etc., can solve the problems of millimeter wave channel sparsity, low rank, etc.

Inactive Publication Date: 2019-11-29
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF2 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of these literatures focus on the estimation of static channels, and only use the sparsity and low rank of millimeter-wave channels alone. Therefore, it is urgent to propose a millimeter-wave time-varying channel estimation algorithm to improve efficiency and performance.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Time-varying channel estimation method based on millimeter wave time-varying channel block sparsity and low rank
  • Time-varying channel estimation method based on millimeter wave time-varying channel block sparsity and low rank
  • Time-varying channel estimation method based on millimeter wave time-varying channel block sparsity and low rank

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0068] The present invention is described in detail below in conjunction with specific examples:

[0069] 1. A time-varying channel estimation method based on millimeter-wave time-varying channel block sparseness and low rank, characterized in that it comprises the following steps:

[0070] S1: In the first phase, the MS sends M 1 A pilot signal is used to estimate the time-varying channel, and the BS uses the receiving matrix to receive it. Specifically, at time t, the MS sends a pilot vector Receiver uses Receive, both vectors are chosen from the unit Gaussian ring. Received M 1 The measured data is expressed as:

[0071] y=Θβ+N

[0072] where Θ is the new measurement matrix, β is the new beam space vector, N is the noise, and the new measurement matrix is ​​as follows

[0073]

[0074] in is the measurement matrix of traditional millimeter-wave channel estimation, and Π is the permutation matrix that translates the data of the same position of the channel at d...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical field of millimeter wave communication, and particularly relates to a time-varying channel estimation method based on millimeter wave time-varying channel blocksparsity and low-rank characteristics. A certain permutation matrix is introduced into a traditional measurement matrix to prove that a millimeter wave time-varying channel has a block sparse characteristic, and then a traditional CP algorithm is compared with a millimeter wave time-varying channel model to prove a low-rank tensor form of the millimeter wave time-varying channel model. On the basis, a two-step algorithm is provided. In the first stage, a traditional block sparse algorithm is used for obtaining non-zero positions and the number, channel angle information is extracted. In the second stage, a tensor decomposition algorithm is used for extracting channel Doppler and gain information, and then millimeter wave MIMO time-varying channels are obtained through integration. Experimental results show that the algorithm provided by the invention is superior to the traditional compressed sensing algorithm and tensor decomposition algorithm, and approaches the theoretical lower limit under certain conditions.

Description

technical field [0001] The invention belongs to the technical field of millimeter wave communication, and in particular relates to a time-varying channel estimation method based on millimeter-wave time-varying channel block sparseness and low rank. Background technique [0002] With the development of ultra-high-definition video transmission, intelligent vehicle communication and virtual reality technology in the future, the capacity of the global mobile communication system will usher in a huge demand. The future demand for data transmission rates may be 1000 times the capacity of existing systems. Millimeter wave communication technology is regarded as a key technology for future wireless networks to meet future high-speed requirements due to its ability to utilize larger communication bandwidths to generate greater transmission rates. For example, in the latest 802 / 11ay standard of IEEE, the 60GHz communication technology can already provide a transmission rate up to 20G...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04B7/0413H04B7/0456H04L25/02
CPCH04B7/0413H04B7/0456H04L25/0202H04L25/024
Inventor 程龙岳光荣熊心宇余代中王志强
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap