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Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission

Authors:

Khizar Anjum,

Zhuoran Qi,

Dario PompiliAuthors Info & Claims

WUWNet '22: Proceedings of the 16th International Conference on Underwater Networks & Systems

Article No.: 29, Pages 1 - 2

https://doi.org/10.1145/3567600.3569542

Published: 29 December 2022 Publication History

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Abstract

Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another ‘language’, depending on the estimated channel conditions.

References

[1]

Khizar Anjum, Zhuoran Qi, and Dario Pompili. 2022. Deep Joint Source-Channel Coding for Underwater Image Transmission. In The 16th International Conference on Underwater Networks & Systems (WUWNet). 1–8.

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[2]

Hovannes Kulhandjian and Tommaso Melodia. 2014. Modeling Underwater Acoustic Channels in Short-Range Shallow Water Environments. In Proceedings of the International Conference on Underwater Networks & Systems (Rome, Italy). 1–5.

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[3]

Konstantinos Pelekanakis, Luca Cazzanti, Giovanni Zappa, and João Alves. 2016. Decision tree-based adaptive modulation for underwater acoustic communications. In 2016 IEEE Third Underwater Communications and Networking Conference (UComms). 1–5.

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[4]

Claude Elwood Shannon. 1948. A mathematical theory of communication. The Bell system technical journal 27, 3 (1948), 379–423.

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[5]

S. Vembu, S. Verdu, and Y. Steinberg. 1995. The source-channel separation theorem revisited. IEEE Transactions on Information Theory 41, 1 (1995), 44–54.

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Published In

WUWNet '22: Proceedings of the 16th International Conference on Underwater Networks & Systems

November 2022

190 pages

ISBN:9781450399524

DOI:10.1145/3567600

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 29 December 2022

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Extended-abstract
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NSF (National Science Foundation)

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WUWNet'22

WUWNet'22: The 16th International Conference on Underwater Networks & Systems

November 14 - 16, 2022

MA, Boston, USA

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Overall Acceptance Rate 84 of 180 submissions, 47%

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Abstract

References

Recommendations

Joint Source and Channel Coding using Trellis Coded CPM: Soft Decoding

Joint source-channel turbo coding for binary Markov sources

LDGM codes for channel coding and joint source-channel coding of correlated sources

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