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New JSCGC paradigm uses generative models for enhanced wireless communication

Researchers have introduced Joint Source-Channel-Generation Coding (JSCGC), a novel communication paradigm that leverages generative models at the receiver. This approach moves beyond traditional rate-distortion theory by reformulating communication as controlled generation, aiming to maximize mutual information under perceptual constraints rather than solely minimizing distortion. Experiments show JSCGC enhances feature-based, semantic, and distributional quality in image transmission, exhibiting semantic inconsistency as a distinct error characteristic. AI

IMPACT Introduces a new generative communication paradigm that could improve data transmission quality and efficiency.

RANK_REASON This is a research paper describing a new technical approach.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Tong Wu, Zhiyong Chen, Guo Lu, Li Song, Feng Yang, Meixia Tao, Wenjun Zhang ·

    JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications

    arXiv:2606.12858v1 Announce Type: cross Abstract: Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distortion theory. However, relying on generic distortio…

  2. arXiv cs.CV TIER_1 English(EN) · Wenjun Zhang ·

    JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications

    Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distortion theory. However, relying on generic distortion metrics fails to capture complex human visual pe…