Residential College | false |
Status | 已發表Published |
A Hybrid Joint Source-Channel Coding Scheme for Mobile Multi-Hop Networks | |
Bian, Chenghong1; Shao, Yulin1,2; Gunduz, Deniz1 | |
2024-08 | |
Conference Name | 2024 IEEE International Conference on Communications (ICC): SAC Machine Learning for Communications and Networking Track |
Source Publication | IEEE International Conference on Communications |
Pages | 986-992 |
Conference Date | 09-13 June 2024 |
Conference Place | Denver, Colorado |
Country | USA |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Abstract | We propose a novel hybrid joint source-channel coding (JSCC) scheme for robust image transmission over multihop networks. In the considered scenario, a mobile user wants to deliver an image to its destination over a mobile cellular network. We assume a practical setting, where the links between the nodes belonging to the mobile core network are stable and of high quality, while the link between the mobile user and the first node (e.g., the access point) is potentially time-varying with poorer quality. In recent years, neural network based JSCC schemes (called DeepJSCC) have emerged as promising solutions to overcome the limitations of separation-based fully digital schemes. However, relying on analog transmission, DeepJSCC suffers from noise accumulation over multi-hop networks. Moreover, most of the hops within the mobile core network may be high-capacity wireless connections, calling for digital approaches. To this end, we propose a hybrid solution, where DeepJSCC is adopted for the first hop, while the received signal at the first relay is digitally compressed and forwarded through the mobile core network. We show through numerical simulations that the proposed scheme is able to outperform both the fully analog and fully digital schemes. Thanks to DeepJSCC it can avoid the cliff effect over the first hop, while also avoiding noise forwarding over the mobile core network thank to digital transmission. We believe this work paves the way for the practical deployment of DeepJSCC solutions in 6G and future wireless networks. |
Keyword | Multi-hop Channel Neural Compression Semantic Communications |
DOI | 10.1109/ICC51166.2024.10622359 |
URL | View the original |
Language | 英語English |
Scopus ID | 2-s2.0-85188935611 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | Faculty of Science and Technology THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
Affiliation | 1.Imperial College London, Department of Electrical and Electronic Engineering, United Kingdom 2.University of Macau, State Key Laboratory of Internet of Things for Smart City, Department of Electrical and Computer Engineering, Macao |
Recommended Citation GB/T 7714 | Bian, Chenghong,Shao, Yulin,Gunduz, Deniz. A Hybrid Joint Source-Channel Coding Scheme for Mobile Multi-Hop Networks[C]:Institute of Electrical and Electronics Engineers Inc., 2024, 986-992. |
APA | Bian, Chenghong., Shao, Yulin., & Gunduz, Deniz (2024). A Hybrid Joint Source-Channel Coding Scheme for Mobile Multi-Hop Networks. IEEE International Conference on Communications, 986-992. |
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