Process-and-forward: deep joint source-channel coding over cooperative relay networks
File(s)
Accepted version
Author(s)
Bian, Chenghong
Shao, Yulin
Wu, Haotian
Ozfatura, Emre
Gündüz, Deniz
Type
Journal Article
Abstract
We introduce deep joint source-channel coding (DeepJSCC) schemes for image transmission over cooperative relay channels. The relay either amplifies-and-forwards its received signal, called DeepJSCC-AF, or leverages neural networks to extract relevant features from its received signal, called DeepJSCC-PF (Process-and-Forward). We consider both half- and full-duplex relays, and propose a novel transformer-based model at the relay. For a half-duplex relay, it is shown that the proposed scheme learns to generate correlated signals at the relay and source to obtain beamforming gains. In the full-duplex case, we introduce a novel block-based transmission strategy, in which the source transmits in blocks, and the relay updates its knowledge about the input signal after each block and generates its own signal. To enhance practicality, a single transformer-based model is used at the relay at each block, together with an adaptive transmission module, which allows the model to seamlessly adapt to different channel qualities and the transmission powers. Simulation results demonstrate the superior performance of DeepJSCC-PF compared to the state-of-the-art BPG image compression algorithm operating at the maximum achievable rate of conventional decode-and-forward and compress-and-forward protocols, in both half- and full-duplex relay scenarios over AWGN and Rayleigh fading channels.
Date Issued
2025-04-01
Date Acceptance
2025-01-01
Citation
IEEE Journal on Selected Areas in Communications, 2025, 43 (4), pp.1118-1134
ISSN
0733-8716
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1118
End Page
1134
Journal / Book Title
IEEE Journal on Selected Areas in Communications
Volume
43
Issue
4
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
2025-01-20