Hybrid Massive MIMO uplink channel estimation method

A technology of channel estimation and estimated value, applied in the direction of digital transmission system, error prevention, electrical components, etc., can solve the problem of channel estimation performance degradation, etc.

Active Publication Date: 2021-09-07
HANGZHOU DIANZI UNIV
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the interval between multiple frequencies of the signal is smaller than a certain threshold, the channel estimation performance will degrade

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
  • Hybrid Massive MIMO uplink channel estimation method
  • Hybrid Massive MIMO uplink channel estimation method
  • Hybrid Massive MIMO uplink channel estimation method

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0053] Simulation example 1: Select the number of antennas N=63, the number of radio frequency chains M=35, the antenna spacing d=λ / 2, the number of channel paths L=3, and the number of Monte Carlo experiments M c =500. The normalized mean square error was used to evaluate the estimation accuracy of the algorithm. The normalized mean square error is defined as: Among them, h es is the channel estimated by each method, and h is the real channel. The channel path gain is set as a random complex gain, and the angle of arrival of the three channel paths is AOA=(80°, 81°, 85°). The antenna at the base station adopts a uniform linear array, the signal-to-noise ratio ranges from -20dB to 10dB, and the grid density of the compressed sensing algorithm OMP is set to Δθ=2°. The algorithm proposed in the present invention is compared with the channel estimation algorithm based on the compressed sensing algorithm OMP and the atomic norm minimization algorithm ANM.

example 2

[0054] Simulation example 2: Select antenna number N=63, antenna spacing d=λ / 2, channel path number L=3, signal-to-noise ratio is 5dB, channel path gain is random complex gain, and the angle of arrival of the three channel paths is AOA= (80°, 81°, 85°), the number of RF chains varies from 30 to 60. The antenna at the base station adopts a uniform linear array, and the number of Monte Carlo experiments is M c =500. The grid density of the compressive sensing algorithm OMP is set to Δθ=2°. The algorithm proposed in the present invention is compared with the channel estimation algorithm based on the compressed sensing algorithm OMP and the atomic norm minimization algorithm ANM.

[0055] Depend on image 3 It can be seen from the normalized mean square error performance comparison diagram that under different SNR conditions, the performance of the algorithm proposed by the present invention is better than that of other algorithms, reflecting the accuracy of the proposed algori...

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 discloses a hybrid Massive MIMO (Multiple Input Multiple Output) uplink channel estimation method. The traditional method has many limitations when processing the problem, such as incapability of single snapshot estimation and the like. The method comprises the following steps: firstly, a mixed Massive MIMO structure is set, and a channel is model; a user side sends a pilot signal, and a base station antenna array receives data to obtain a sampling signal; the user side does not send a pilot signal, and the base station antenna array receives a noise signal; and an optimization problem is designed based on the reconstructed Hankel matrix to solve and obtain an estimated value of the channel. According to the method disclosed by the invention, channel estimation can be carried out only by single snapshot data without estimating the path number of the channel, and meanwhile, the base mismatching problem and the signal frequency interval limitation of a traditional compressed sensing method can be avoided. According to the method, when the base station antenna array element receives the data, the noise parameter of the base station receiver is obtained, so that the model has the denoising capability, and the accuracy of channel estimation is improved.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and relates to a hybrid Massive MIMO uplink channel estimation method, in particular to a hybrid Massive MIMO uplink channel estimation method based on reconstructed Hankel matrix. Background technique [0002] Massive MIMO (Massive Multi-input Multi-output) is one of the key technologies of the 5G mobile communication system, which has the advantages of high spectral efficiency and high energy efficiency. Since the millimeter wave frequency band can provide a large bandwidth, the combination of Massive MIMO and millimeter wave has attractive application prospects. But in the traditional Massive MIMO structure, each antenna needs to be connected to a radio frequency link. Since the number of antenna elements is usually very large, the base station will need to deploy a large number of radio frequency chains, which will further increase the system hardware deployment cost and power...

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): H04B7/0452H04L1/00
CPCH04B7/0452H04L1/0048
Inventor 潘玉剑王锋
Owner HANGZHOU DIANZI UNIV
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