CDDM: Channel Denoising Diffusion Models for Wireless Semantic Communications
On the map: Diffusion models → Diffusion for compression and wireless
Abstract (arXiv)
Diffusion models (DM) can gradually learn to remove noise, which have been widely used in artificial intelligence generated content (AIGC) in recent years. The property of DM for eliminating noise leads us to wonder whether DM can be applied to wireless communications to help the receiver mitigate the channel noise. To address this, we propose channel denoising diffusion models (CDDM) for semantic communications over wireless channels in this paper. CDDM can be applied as a new physical layer module after the channel equalization to learn the distribution of the channel input signal, and then utilizes this learned knowledge to remove the channel noise. We derive corresponding training and sampling algorithms of CDDM according to the forward diffusion process specially designed to adapt the channel models and theoretically prove that the well-trained CDDM can effectively reduce the conditional entropy of the received signal under small sampling steps. Moreover, we apply CDDM to a semantic communications system based on joint source-channel coding (JSCC) for image transmission. Extensive experimental results demonstrate that CDDM can further reduce the mean square error (MSE) after minimum mean square error (MMSE) equalizer, and the joint CDDM and JSCC system achieves better performance than the JSCC system and the traditional JPEG2000 with low-density parity-check (LDPC) code approach.
Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). Placed in Diffusion for compression and wireless, one of 14 directions in Diffusion models. Builds on 32 of its 52 references that are in the map. First posted on arXiv 16 Sep 2023.
Builds on
32 of 52 references.
Closest ancestors · 4
Same direction, newest first
- 2023Diffusion models for audio semantic communication13 Sep
- 2023Generative Semantic Communication: Diffusion Models Beyond Bit Recovery7 Jun
- 2023CDDM: Channel Denoising Diffusion Models for Wireless Communications16 May
- 2022Denoising Diffusion Error Correction Codes16 Sep
Other references · 28
- 2017Attention Is All You Needcited by 59,932
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
- 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
- 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
- 2016Wide Residual Networkscited by 3,057
- 2015Variational Inference with Normalizing Flowscited by 2,161
- 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
16 more
- 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
- 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
- 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
- 2022Is Conditional Generative Modeling all you need for Decision-Making?cited by 504
- 2023On the Importance of Noise Scheduling for Diffusion Modelscited by 193
- 2023Video Probabilistic Diffusion Models in Projected Latent Spacecited by 171
- 2023A Reparameterized Discrete Diffusion Model for Text Generationcited by 152
- 2022Semantic Communications for Future Internet: Fundamentals, Applications, and Challengescited by 94
- 2021Nonlinear Transform Source-Channel Coding for Semantic Communicationscited by 73
- 2023MADiff: Offline Multi-agent Learning with Diffusion Modelscited by 73
- 2021What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligencecited by 48
- 2022Deep Joint Source-Channel Coding for Semantic Communicationscited by 40
- 2018Deep Joint Source-Channel Coding for Wireless Image Transmissioncited by 38
- 2022WITT: A Wireless Image Transmission Transformer for Semantic Communicationscited by 36
- 2023AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharingcited by 21
- 2022Learning Based Joint Coding-Modulation for Digital Semantic Communication Systemscited by 5
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Citing papers per year: 2023: 1; 2024: 17; 2025: 24; 2026: 16.
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