This paper introduces a novel method for transmitting video data over noisy wireless channels with high efficiency and controllability. The method derivates from model division multiple access (MDMA) to extract common semantic features from video frames. It also uses deep joint source-channel coding (JSCC) as the main framework to establish communication links and deal with channel noise. An entropy-based variable length coding scheme is developed to adjust the data amount accurately and explicitly. We name our method as model division video semantic communication (MDVSC). The main steps of our approach are as follows: first, video frames are transformed into a latent space to reduce computational complexity and redistribute data. Then, common features and individual features are extracted, and variable length coding is applied to further eliminate redundant semantic information under the communication bandwidth constraint. We evaluate our method on standard video test sequences and compare it with traditional wireless video coding methods. The results show that MDVSC generally surpasses the conventional methods in terms of quality metrics and has the capability to control code length precisely. Moreover, additional experiments and ablation studies are conducted to demonstrate its potential for various tasks.

翻译：本文提出了一种在噪声无线信道上高效且可控地传输视频数据的新方法。该方法源自模型分割多址接入（MDMA），用于从视频帧中提取公共语义特征。同时，采用深度联合信源信道编码（JSCC）作为主要框架来建立通信链路并应对信道噪声。我们开发了一种基于熵的可变长度编码方案，以精确且显式地调整数据量。将该方法命名为模型分割视频语义通信（MDVSC）。该方法的主要步骤如下：首先，将视频帧转换到潜在空间以降低计算复杂度并重新分配数据；然后提取公共特征和个体特征，并在通信带宽约束下应用可变长度编码进一步消除冗余语义信息。我们在标准视频测试序列上对该方法进行评估，并与传统无线视频编码方法进行比较。结果表明，MDVSC在质量指标上通常优于传统方法，并具备精确控制码长的能力。此外，通过额外实验和消融研究，验证了该方法在多种任务中的应用潜力。