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SCSC: a novel standards-compatible semantic communication framework for image transmission
File(s)
HWGFSG_TCOM25.pdf (15.47 MB)
Accepted version
Author(s)
Han, Xue
Wu, Yongpeng
Gao, Zhen
Feng, Biqian
Shi, Yuxuan
Type
Journal Article
Abstract
Joint source-channel coding (JSCC) is a promising paradigm for next-generation communication systems, particularly in challenging transmission environments. In this paper, we propose a novel standard-compatible JSCC framework for the transmission of images over multiple-input multiple-output (MIMO) channels. Different from the existing end-to-end AI-based DeepJSCC schemes, our framework consists of learnable modules that enable communication using conventional separate source and channel codes (SSCC), which makes it amenable for easy deployment on legacy systems. Specifically, the learnable modules involve a preprocessing-empowered network (PPEN) for preserving essential semantic information, and a precoder & combiner-enhanced network (PCEN) for efficient transmission over a resource-constrained MIMO channel. We treat existing compression and channel coding modules as non-trainable blocks. Since the parameters of these modules are non-differentiable, we employ a proxy network that mimics their operations when training the learnable modules. Numerical results demonstrate that our scheme can save more than 29% of the channel bandwidth, and requires lower complexity compared to the constrained baselines. We also show its generalization capability to unseen datasets and tasks through extensive experiments.
Date Issued
2025-08-01
Date Acceptance
2025-01-01
Citation
IEEE Transactions on Communications, 2025, 73 (8), pp.5682-5698
URI
URL
DOI
ISSN
0090-6778
Publisher
Institute of Electrical and Electronics Engineers
Start Page
5682
End Page
5698
Journal / Book Title
IEEE Transactions on Communications
Volume
73
Issue
8
Copyright Statement
Copyright © 2025 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published
Date Publish Online
2025-01-13