mlsanityData to 7 Oct 2026

Transformer-aided Wireless Image Transmission with Channel Feedback

arXiv 2306.09101 ↗First posted 15 Jun 2023cs.IT eess.SP math.ITcited by 19

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Abstract (arXiv)

This paper presents a novel wireless image transmission paradigm that can exploit feedback from the receiver, called DeepJSCC-ViT-f. We consider a block feedback channel model, where the transmitter receives noiseless/noisy channel output feedback after each block. The proposed scheme employs a single encoder to facilitate transmission over multiple blocks, refining the receiver's estimation at each block. Specifically, the unified encoder of DeepJSCC-ViT-f can leverage the semantic information from the source image, and acquire channel state information and the decoder's current belief about the source image from the feedback signal to generate coded symbols at each block. Numerical experiments show that our DeepJSCC-ViT-f scheme achieves state-of-the-art transmission performance with robustness to noise in the feedback link. Additionally, DeepJSCC-ViT-f can adapt to the channel condition directly through feedback without the need for separate channel estimation. We further extend the scope of the DeepJSCC-ViT-f approach to include the broadcast channel, which enables the transmitter to generate broadcast codes in accordance with signal semantics and channel feedback from individual receivers.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 11; 2025: 6; 2026: 2.

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  1. 2024Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designscited by 32
  2. 2025Semantics-Guided Diffusion for Deep Joint Source-Channel Coding in Wireless Image Transmissioncited by 15
  3. 2024Diffusion-Aided Joint Source Channel Coding For High Realism Wireless Image Transmissioncited by 11
  4. 2024Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and their Enabling Semantic Applicationscited by 6
  5. 2025SING: Semantic Image Communications using Null-Space and INN-Guided Diffusion Modelscited by 5
  6. 2024Transformer-Aided Semantic Communicationscited by 3
  7. 2024Rate-Adaptive Generative Semantic Communication Using Conditional Diffusion Modelscited by 3
  8. 2024Efficient Semantic Communication Through Transformer-Aided Compressioncited by 3
  9. 2024Generative Semantic Communication for Text-to-Speech Synthesiscited by 2
  10. 2024Deep Learning-Based Image Compression for Wireless Communications: Impacts on Reliability,Throughput, and Latencycited by 2
  11. 2024Learned Image Transmission with Hierarchical Variational Autoencodercited by 1
  12. 2025SNR-EQ-JSCC: Joint Source-Channel Coding with SNR-Based Embedding and Querycited by 1
7 more
  1. 2025SecDiff: Diffusion-Aided Secure Deep Joint Source-Channel Coding Against Adversarial Attackscited by 1
  2. 2024Interplay of Semantic Communication and Knowledge Learningcited by 0
  3. 2024Variational Source-Channel Coding for Semantic Communicationcited by 0
  4. 2025A Channel-Triggered Backdoor Attack on Wireless Semantic Image Reconstructioncited by 0
  5. 2025Optimization of Private Semantic Communication Performance: An Uncooperative Covert Communication Methodcited by 0
  6. 2026Adaptive Semantic Communication for Wireless Image Transmission Leveraging Mixture-of-Experts Mechanismcited by 0
  7. 2026TISC: A Text-Driven Image Semantic Communication System for Faithful Reconstructioncited by 0