Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

OFDM channel estimation method based on depth feature fusion network

A deep feature and channel estimation technology, applied in the field of OFDM channel estimation, can solve the problem that the model is not enough to meet the requirements, and achieve the effect of reducing influence, data distortion and channel noise

Active Publication Date: 2019-01-15
STATE GRID CORP OF CHINA +2
View PDF8 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For the channel distortion problem, in the case of rich pilots, cyclic prefix (Cyclic Prefix, CP) and linear noise, the traditional estimation method and its improvement can meet the system requirements, but in the case of limited pilots, CP removal and In the case of nonlinear noise, the previous models are not enough to meet the requirements

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
  • OFDM channel estimation method based on depth feature fusion network
  • OFDM channel estimation method based on depth feature fusion network
  • OFDM channel estimation method based on depth feature fusion network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0029] Such as figure 1 As shown, a kind of OFDM channel estimation method based on deep feature fusion network provided by the present invention comprises steps:

[0030] S1: At the transmitting end, the pilot is inserted into the original transmission signal; in this embodiment, the OFDM channel system applied by the deep feature fusion network-based OFDM channel estimation method is the same as the traditional baseband OFDM system, consisting of the transmitting end, OFDM channel and The receiving end is composed of three parts, and the original transmission signal is a modulated transmission signal, which is the prior art and will not be described here. The pilot symbol is inserted at the front end of the OFDM block, that is, the original transmission signal, and forms a new transmission signal with the original transmission signal, and proceeds to step S2.

[0031] S2: change the transmission signal serial data flow obtained in step S1 into a parallel data flow, and then...

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 provides an OFDM channel estimation method based on a depth feature fusion network, which comprises the following steps: S1, inserting a pilot into an original transmission signal; S2, the serial data stream of the transmission signal obtained in the step S1 is changed into a parallel data stream, and the transmission signal is OFDM modulated by the IDFT; 3, chan a transmission signal from a parallel data stream to a serial data stream; Transmitting to a receiving end via an OFDM channel; 4, aft receiving that transmission signal, the receive end changes the transmission signal from the serial data stream to the parallel data stream, and then demodulates the transmission signal by using the DFT; 5, chan a transmission signal from a parallel data stream to a serial data stream, inputting that transmission signal into a channel estimation model of a depth characteristic fusion network, and output the transmission signal fused by the channel estimation model; The invention can effectively recover the transmission signal in the OFDM channel under the condition of limited pilot frequency, CP removal and non-linear noise while ensuring the performance of channel estimation,thereby reducing the influence of data distortion and channel noise.

Description

technical field [0001] The invention relates to the field of OFDM channel estimation, in particular to an OFDM channel estimation method based on a deep feature fusion network. Background technique [0002] Orthogonal Frequency-division Multiplexing (OFDM) is a popular multi-carrier modulation method, which overcomes frequency-selective fading in wireless channels by reducing and eliminating signal intersymbol interference. Widely used in wireless broadband systems. In an OFDM system, channel state information (ChannelState Information, CSI) is closely related to coherent demodulation and decoding. In the previous studies, the CSI is usually estimated according to the pilot before the transmitted data is detected, and the data and symbols transmitted in the channel are recovered in the receiver by estimating the CSI. [0003] In previous historical studies, channel estimation in OFDM systems has been extensively studied by researchers. From the initial traditional estimat...

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): H04L25/02
CPCH04L25/0224H04L25/0254
Inventor 艾乾可吴维农刘国金秦骁戴诚田博今陈聿
Owner STATE GRID CORP OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com