MDVSC -- Wireless Model Division Video Semantic Communication

TL;DR

This paper introduces MDVSC, a novel wireless video communication framework that leverages model division multiple access and deep joint source-channel coding to enhance transmission efficiency and quality over noisy channels.

Contribution

It presents a new end-to-end learnable system combining model division, semantic feature extraction, and entropy coding for efficient wireless video transmission.

Findings

Outperforms traditional schemes in perceptual quality metrics.

Effectively controls code length under bandwidth constraints.

Demonstrates robustness over noisy channels.

Abstract

In this paper, we propose a new wireless video communication scheme to achieve high-efficiency video transmission over noisy channels. It exploits the idea of model division multiple access (MDMA) and extracts common semantic features across video frames. Besides, deep joint source-channel coding (JSCC) is applied to overcome the distortion caused by noisy channels. The proposed framework is collected under the name model division video semantic communication (MDVSC). In particular, temporal relative video frames are first transformed into a latent space for computing complexity reduction and data redistribution. Accordingly, a novel entropy-based variable length coding is developed further to compress semantic information under the communication bandwidth cost limitation. The whole MDVSC is an end-to-end learnable system. It can be formulated as an optimization problem whose goal is to minimize end-to-end transmission distortion under restricted communication resources. Across standard video source test sequences, test results show that the MDVSC outperforms traditional wireless video coding schemes generally under perceptual quality metrics and has the ability to control code length precisely.