  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.
