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Deep Learning Aided Joint Source-Channel Coding for Wireless Networks

2021 IEEE/CIC International Conference on Communications in China (ICCC), 2021
Wireless image transmission and estimation techniques have found a variety of applications in 5G Internet of Things (IoT) under the finite block length transmissions. However, the traditional digital transmission scheme is known to suffer from the “cliff effect”.
Jintao Yan, Jianhao Huang, Chuan Huang
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D²-JSCC: Digital Deep Joint Source-Channel Coding for Semantic Communications

IEEE Journal on Selected Areas in Communications
Jianhao Huang   +3 more
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Deep joint source-channel coding for semantic communication

The evolution of artificial intelligence applications has exponentially increased the demand for efficient and low-latency transmission of large data volumes, posing significant challenges to conventional wireless communication systems. While conventional systems, known for simplicity and elegance, have been extensively studied with a focus on reliable
openaire   +1 more source

Deep Joint Source-Channel Coding for Underwater Image Transmission

Proceedings of the 16th International Conference on Underwater Networks & Systems, 2022
Khizar Anjum, Zhuoran Qi, Dario Pompili
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Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission

Proceedings of the 16th International Conference on Underwater Networks & Systems, 2022
Khizar Anjum, Zhuoran Qi, Dario Pompili
openaire   +1 more source

Nonlinear Transform Source-Channel Coding for Semantic Communications

IEEE Journal on Selected Areas in Communications, 2022
Jincheng Dai, Wang Sixian, Zhongwei Si
exaly  

Deep Joint Source-Channel Coding for CSI Feedback: An End-to-End Approach

IEEE Journal on Selected Areas in Communications, 2023
Jialong Xu, Bo Ai, Ning Wang
exaly  

Low-Delay Analog Joint Source-Channel Coding With Deep Learning

IEEE Transactions on Communications, 2023
Ziwei Xuan, Krishna Narayanan
openaire   +1 more source

Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules

IEEE Transactions on Circuits and Systems for Video Technology, 2022
Jialong Xu, Bo Ai, Wei Chen
exaly  

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