ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding

[2608.15066] ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Electrical Engineering and Systems Science > Signal Processing arXiv:2608.15066 (eess) [Submitted on 15 Aug 2026] Title: ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding Authors: Kemi Chen , Mingkai Chen , Youjia Chen , Qian Liu , Wei Gao , Tiesong Zhao View a PDF of the paper titled ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding, by Kemi Chen and 5 other authors View PDF HTML (experimental) Abstract: Multimodal signals, such as visual, audio, and tactile data, are increasingly maintained as persistent digital assets in immersive communication systems and digital twins. In these settings, the same multimodal content is repeatedly accessed by heterogeneous receivers with varying modality and bandwidth requirements. Existing compression and Joint Source-Channel Coding (JSCC) methods typically follow a per-request encoding paradigm, resulting in redundant computation and low efficiency during repeated access. To address this issue, we propose ParaJSCC, a multimodal JSCC framework designed for reusable representation serving. ParaJSCC converts each multimodal sample offline at the cloud/content server into a compact, quantized parameter package, which is then stored at the edge serving node for low-latency access. During serving, only the subset required by the current request is transmitted over the wireless channel, followed by lightweight decoding at the receiver. The framework employs a progressive shared-private parameterization to support modality-selective transmission and scalable reconstruction under varying bandwidth constraints. Experiments on multimodal datasets show that ParaJSCC significantly reduces online latency (e.g., from 17.18~ms to 4.34~ms for image-only requests and from 43.96~ms to 11.21~ms for full multimodal requests) and transmission rate (by 47.8\%--51.2\% for selective requests), while maintaining strong reconstruction quality under noisy channels. Subjects: Signal Processing (eess.SP) ; Multimedia (cs.MM); Image and Video Processing (eess.IV) Cite as: arXiv:2608.15066 [eess.SP] (or arXiv:2608.15066v1 [eess.SP] for this version) https://doi.org/10.48550/arXiv.2608.15066 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Kemi Chen [ view email ] [v1] Sat, 15 Aug 2026 06:35:11 UTC (5,506 KB) Full-text links: Access Paper: View a PDF of the paper titled ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding, by Kemi Chen and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: eess.SP < prev | next > new | recent | 2026-08 Change to browse by: cs cs.MM eess eess.IV References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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