The sixth-generation mobile communication system proposes the vision of smart interconnection of everything, which requires accomplishing communication tasks while ensuring the performance of intelligent tasks. A joint source-channel coding method based on semantic importance is proposed, which aims at preserving semantic information during wireless image transmission and thereby boosting the performance of intelligent tasks for images at the receiver. Specifically, we first propose semantic importance weight calculation method, which is based on the gradient of intelligent task’s perception results with respect to the features. Then, we design the semantic loss function in the way of using semantic weights to weight the features. Finally, we train the deep joint source-channel coding network using the semantic loss function. Experiment results demonstrate that the proposed method achieves up to 57.7% and 9.1% improvement in terms of intelligent task’s performance compared with the source-channel separation coding method and the deep source-channel joint coding method without considering semantics at the same compression rate and signal-to-noise ratio, respectively.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep Joint Source-Channel Coding for Wireless Image Transmission with Semantic Importance


    Contributors:
    Sun, Qizheng (author) / Guo, Caili (author) / Yang, Yang (author) / Chen, Jiujiu (author) / Tang, Rui (author) / Liu, Chuanhong (author)


    Publication date :

    2022-09-01


    Size :

    3287123 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Analog Joint Source Channel Coding for Wireless Optical Communications and Image Transmission

    Romero, S.M. / Hassanin, M. / Garcia-Frias, J. et al. | British Library Online Contents | 2014


    Implementation of Deep Joint Source-Channel Coding on 5G Systems for Image Transmission

    Matsumoto, Keigo / Inoue, Yoshiaki / Hara-Azumi, Yuko et al. | IEEE | 2023


    Deep Semantic Coding for Wireless Image Retrieval

    Wang, Ying / Qi, Chenhao | IEEE | 2022


    Joint source/channel coding for wireless channels

    Goldsmith,A. / California Inst.of Technol.,US | Automotive engineering | 1995


    Robust airborne image transmission using joint source-channel coding with UEP

    Li, Lun / Wang, Gang / Chen, Genshe et al. | IEEE | 2016