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VQ-VAE Empowered Wireless Communication for Joint Source-Channel Coding and Beyond

conference contribution
posted on 2024-03-27, 02:37 authored by M Nemati, Jihong ParkJihong Park, Jinho ChoiJinho Choi
Vector Quantized Variational Autoencoder (VQ-VAE) has shown promise in representing diverse and complex data distributions in deep learning, making it a potential solution for various applications including wireless communications. In this paper, we propose a joint source-channel coding scheme based on VQ-VAE for point-to-point wireless communication. Our approach leverages the dependence of the encoder and decoder on a given dataset and channel conditions to develop efficient encoding and decoding schemes, leading to improved reliability and efficiency even in the presence of noisy wireless channels. We demonstrate the effectiveness of our proposed approach through extensive simulations in handling realistic wireless communication scenarios. In addition, we discuss potential connections to semantic communication and highlight the secure and energy-efficient nature of our approach.

History

Volume

00

Pagination

3155-3160

Location

Kuala Lumpur, Malaysia

Start date

2023-12-04

End date

2023-12-08

ISSN

2334-0983

eISSN

2576-6813

ISBN-13

9798350310900

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

Proceedings - IEEE Global Communications Conference, GLOBECOM

Event

GLOBECOM 2023 - 2023 IEEE Global Communications Conference

Publisher

IEEE

Place of publication

Piscataway, N.J.

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