Results 11 to 20 of about 96,557 (255)
Deep Joint Source-Channel Coding for Wireless Image Transmission [PDF]
IEEE Transactions on Cognitive Communications and Networking, 2019 To appear in IEEE Transactions on Cognitive Communications and ...
Eirina Bourtsoulatze +2 more
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Deep Joint Source-Channel Coding for Semantic Communications
IEEE Communications Magazine, 2023 Semantic communications is considered as a promising technology to increase the efficiency of next-generation communication systems, particularly targeting human-machine and machine-type communications. In contrast to the source-agnostic approach of conventional wireless communication systems, semantic communication seeks to ensure that only the ...
Xu, Jialong +5 more
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DeepJSCC-Q: Constellation Constrained Deep Joint Source-Channel Coding
IEEE Journal on Selected Areas in Information Theory, 2022 Recent works have shown that modern machine learning techniques can provide an alternative approach to the long-standing joint source-channel coding (JSCC) problem. Very promising initial results, superior to popular digital schemes that utilize separate source and channel codes, have been demonstrated for wireless image and video transmission using ...
Tze-Yang Tung +3 more
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OFDM-Guided Deep Joint Source Channel Coding for Wireless Multipath Fading Channels [PDF]
IEEE Transactions on Cognitive Communications and Networking, 2022 16 pages, 17 figures.
Mingyu Yang +2 more
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Deep Joint Source-Channel Coding for Image Transmission With Visual Protection
IEEE Transactions on Cognitive Communications and Networking, 2023 Joint source-channel coding (JSCC) has achieved great success due to the introduction of deep learning (DL). Compared to traditional separate source-channel coding (SSCC) schemes, the advantages of DL-based JSCC (DJSCC) include high spectrum efficiency, high reconstruction quality, and relief of "cliff effect".
Jialong Xu +4 more
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SwinJSCC: Taming Swin Transformer for Deep Joint Source-Channel Coding
IEEE Transactions on Cognitive Communications and NetworkingAs one of the key techniques to realize semantic communications, end-to-end optimized neural joint source-channel coding (JSCC) has made great progress over the past few years. A general trend in many recent works pushing the model adaptability or the application diversity of neural JSCC is based on the convolutional neural network (CNN) backbone ...
Ke Yang +5 more
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Deep Joint Source-Channel Coding for Adaptive Image Transmission Over MIMO Channels
IEEE Transactions on Wireless CommunicationsThis paper introduces a vision transformer (ViT)-based deep joint source and channel coding (DeepJSCC) scheme for wireless image transmission over multiple-input multiple-output (MIMO) channels, denoted as DeepJSCC-MIMO. We consider DeepJSCC-MIMO for adaptive image transmission in both open-loop and closed-loop MIMO systems.
Haotian Wu +4 more
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Constellation Design for Deep Joint Source-Channel Coding
IEEE Signal Processing Letters, 2022 Deep learning-based joint source-channel coding (JSCC) has shown excellent performance in image and feature transmission. However, the output values of the JSCC encoder are continuous, which makes the constellation of modulation complex and dense.
Mengyang Wang +3 more
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DeepJSCC-f: Deep Joint Source-Channel Coding of Images With Feedback [PDF]
IEEE Journal on Selected Areas in Information Theory, 2020 We consider wireless transmission of images in the presence of channel output feedback. From a Shannon theoretic perspective feedback does not improve the asymptotic end-to-end performance, and separate source coding followed by capacity-achieving channel coding, which ignores the feedback signal, achieves the optimal performance. It is well known that
David Burth Kurka, Deniz Gunduz
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SNR-Adaptive Deep Joint Source-Channel Coding for Wireless Image Transmission [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Considering the problem of joint source-channel coding (JSCC) for multi-user transmission of images over noisy channels, an autoencoder-based novel deep joint source-channel coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can estimate the signal-to-noise ratio (SNR) and use it to adaptively decode the transmitted image.
Ding, Mingze +3 more
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