Predictive and Adaptive Deep Coding for Wireless Image Transmission in Semantic Communication

Zhang, Wenyu; Zhang, Haijun; Ma, Hui; Shao, Hua; Wang, Ning; Leung, Victor C. M.

doi:10.1109/twc.2023.3234408

articleIEEE Transactions on Wireless CommunicationsJan 11, 2023Closed access

Predictive and Adaptive Deep Coding for Wireless Image Transmission in Semantic Communication

WZWenyu Zhang HZHaijun Zhang HMHui Ma HSHua Shao NWNing Wang

University of Science and Technology Beijing · Zhengzhou University · +2 more institutions

Indexed incrossref

Abstract

Semantic communication is a newly emerged communication paradigm that exploits deep learning (DL) models to realize communication processes like source coding and channel coding. Recent advances have demonstrated that DL-based joint source-channel coding (DeepJSCC) can achieve exciting data compression and noise-resiliency performances for wireless image transmission tasks, especially in environments with low channel signal-to-noises (SNRs). However, existing DeepJSCC-based semantic communication frameworks still cannot achieve adaptive code rates for different channel SNRs and image contents, which reduces its flexibility and bandwidth efficiency. In this paper, we propose a predictive and adaptive deep…

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189

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FWCI: 31.29
Percentile: 100%
References: 38

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Topics

Keywords

Computer science
Coding (social sciences)
Wireless
Forward error correction
Channel (broadcasting)
Computer engineering
Image compression
Image quality

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