Multi-scale Feature Extraction Channel Equalization Method Based on Res2net Module

Under the condition of time-varying multi-path channel, to address traditional channel equalization methods cannot effectively eliminate Inter Symbol Interference, a multi-scale feature extraction channel equalization method based on Res2net module is proposed. The method adopts Res2net network tech...

Full description

Saved in:
Bibliographic Details
Published in2024 2nd International Conference on Signal Processing and Intelligent Computing (SPIC) pp. 116 - 120
Main Authors Wang, Yi, Zhou, Fan, Su, Heng
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.09.2024
Subjects
Bit error rate
Channel equalization
Colored noise
Communication systems
Feature extraction
Inter Symbol Interference
Interference
Multi-scale feature extraction
Rayleigh channels
Reliability
Res2net
Residual thought
Simulation
Symbols
White noise
Online AccessGet full text

Cover

More Information
Summary:Under the condition of time-varying multi-path channel, to address traditional channel equalization methods cannot effectively eliminate Inter Symbol Interference, a multi-scale feature extraction channel equalization method based on Res2net module is proposed. The method adopts Res2net network technology, firstly, multi-scale feature extraction is carried out in the high dimensional space for the components of the received signal that are subject to ISI, then the reconstruction of the interference signal is completed by the extracted multi-scale features, and finally, based on the idea of residual difference, the reconstructed interference signal is used to correct and compensate the received signal in order to achieve the channel equalization, which reduces the bit error rate of the communication system and improves the reliability of the transmission of the communication system. Simulation results show that, compared with the traditional channel equalization method, the proposed method reduces the bit error rate by 6% in the Gaussian white noise channel environment and 3% in the colored noise channel environment under the multi-path Rayleigh channel.
DOI:10.1109/SPIC62469.2024.10691400