SCDM：用于数字语义通信的基于分数的信道去噪模型
SCDM: Score-Based Channel Denoising Model for Digital Semantic Communications
AI总结：
本文提出用于数字语义通信的基于分数的信道去噪模型SCDM，通过将星座符号失真建模为前向扩散过程并定制前向噪声以匹配数字信道特性，有效对接收符号去噪，显著提升低信噪比下的重建鲁棒性并大幅降低存储需求。
摘要：
基于分数的扩散模型是扩散模型家族中的一个重要变体，在日益流行的生成任务领域得到了广泛应用。最近的研究探索了扩散模型在语义通信中的去噪潜力。然而，在以往的范式中，扩散过程中的噪声失真与数字信道噪声特性并不精确匹配。在本研究中，我们为数字语义通信（DSC）引入了基于分数的信道去噪模型（SCDM）。SCDM将数字传输中星座符号序列的失真视为基于分数的前向扩散过程。我们设计了定制的前向噪声破坏，以在训练阶段对齐数字信道噪声属性。在推理阶段，训练良好的SCDM能够在各种SNR条件下有效地对接收到的语义符号进行去噪，降低了语义解码器从接收到的噪声符号中提取语义信息的难度，从而增强了重建语义信息的鲁棒性。实验结果表明，SCDM在PSNR、SSIM和MSE指标上优于基线模型，特别是在低SNR水平下表现突出。此外，SCDM将存储需求降低了7.8倍。这种存储效率结合其强大的去噪能力，使SCDM成为在各种信道条件下DSC的实用解决方案。
英文摘要：
Score-based diffusion models represent a significant variant within the diffusion model family and have seen extensive application in the increasingly popular domain of generative tasks. Recent investigations have explored the denoising potential of diffusion models in semantic communications. However, in previous paradigms, noise distortion in the diffusion process does not match precisely with digital channel noise characteristics. In this work, we introduce the Score-Based Channel Denoising Model (SCDM) for Digital Semantic Communications (DSC). SCDM views the distortion of constellation symbol sequences in digital transmission as a score-based forward diffusion process. We design a tailored forward noise corruption to align digital channel noise properties in the training phase. During the inference stage, the well-trained SCDM can effectively denoise received semantic symbols under various SNR conditions, reducing the difficulty for the semantic decoder in extracting semantic information from the received noisy symbols and thereby enhancing the robustness of the reconstructed semantic information. Experimental results show that SCDM outperforms the baseline model in PSNR, SSIM, and MSE metrics, particularly at low SNR levels. Moreover, SCDM reduces storage requirements by a factor of 7.8. This efficiency in storage, combined with its robust denoising capability, makes SCDM a practical solution for DSC across diverse channel conditions.
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