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When Transformer Meets CSI Feedback in mMIMO Systems: A Lightweight CsiMobileViT Approach

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accurate channel state information (CSI) feedback is essential in frequency division duplex massive multiple-input multiple-output systems, but increasing antennas cause the CSI matrix to grow exponentially, leading to significant feedback overhead. Inspired by the success of Transformers in natural language processing, recent Transformer-based CSI feedback methods have achieved excellent performance, though often with high computational costs that hinder real-time deployment on terminal devices. To address this challenge, in this paper, we present CsiMobileVit, a lightweight network that lowers computational complexity while maintaining reconstruction accuracy. The method achieves a good balance between simplicity and accuracy, making it practical for resource-limited devices. Extensive experiments confirm the effectiveness of this network.

Original languageEnglish
Title of host publication2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331503208
DOIs
Publication statusPublished - 2025
Event2025 IEEE 102nd Vehicular Technology Conference, VTC 2025 - Chengdu, China
Duration: 19 Oct 202522 Oct 2025

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1090-3038

Conference

Conference2025 IEEE 102nd Vehicular Technology Conference, VTC 2025
Country/TerritoryChina
CityChengdu
Period19/10/2522/10/25

Keywords

  • CSI feedback
  • deep learning
  • massive MIMO
  • MobileViT
  • Transformer

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