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.

翻译：本文提出了一种新型无线视频通信方案，旨在实现噪声信道下的高效视频传输。该方案利用模型分割多址接入（MDMA）理念，提取视频帧间的通用语义特征，并采用深度联合信源信道编码（JSCC）克服噪声信道引起的失真。所提框架统称为模型分割视频语义通信（MDVSC）。具体而言，首先将时间关联的视频帧转换至潜在空间，以降低计算复杂度并实现数据再分配；进而基于熵开发出新型变长编码方法，在通信带宽成本约束下压缩语义信息。整个MDVSC系统具备端到端可学习特性，可建模为在受限通信资源下最小化端到端传输失真的优化问题。在标准视频源测试序列上的实验结果表明，MDVSC在感知质量指标上普遍优于传统无线视频编码方案，且具备精确控制码长的能力。