2025/12/24 by Haotian Wu, Wu, Haotian, Gen Li +5
Computer Science · #68P30 #94A08 #Advanced Data Compression Techniques #Digital Media Forensic Detection #E.4 #FOS: Computer and information sciences #FOS: Electrical engineering #I.4.2 #Image and Video Processing (eess.IV) #Information Theory (cs.IT) #Wireless Signal Modulation Classification #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2512.20981
openalex publication_date 2025/12/24 · openalex created_date 2025/12/26 · openalex updated_date 2026/07/28
This paper introduces Implicit-JSCC, a novel overfitted joint source-channel coding paradigm that directly optimizes channel symbols and a lightweight neural decoder for each source. This instance-specific strategy eliminates the need for training datasets or pre-trained models, enabling a storage-free, modality-agnostic solution. As a low-complexity alternative, Implicit-JSCC achieves efficient image transmission with around 1000x lower decoding complexity, using as few as 607 model parameters and 641 multiplications per pixel. This overfitted design inherently addresses source generalizability and achieves state-of-the-art results in the high SNR regimes, underscoring its promise for future communication systems, especially streaming scenarios where one-time offline encoding supports multiple online decoding.