This paper proposes a MIMO-OFDM-based context video semantic transmission framework, namely M-CVST, for robust video communication over multi-path multiple-input multiple-output (MIMO) channels. It introduces a context-subcarrier correlation map that aligns video feature context with groups of MIMO subcarriers. To leverage the time-correlated nature of multi-path channels, a recursive subcarrier sampling method paired with time-correlated reference embedding is designed, enabling the use of previously sampled MIMO subcarrier CSI to enhance channel state awareness in the entropy coding model. Numerical results verify the superiority of proposed M-CVST over MIMO multi-path channels compared to other semantic schemes and traditional separated schemes.

翻译：本文提出一种基于MIMO-OFDM的上下文视频语义传输框架，命名为M-CVST，用于在多径多输入多输出(MIMO)信道上实现鲁棒视频通信。该框架引入一种上下文-子载波关联图，将视频特征上下文与MIMO子载波组对齐。为利用多径信道的时间相关性，设计了一种递归子采样方法与时间相关参考嵌入相结合的技术，使得熵编码模型能够利用先前采样的MIMO子载波信道状态信息(CSI)来增强信道感知能力。数值结果验证了所提出的M-CVST相比其他语义方案与传统分离方案在多径MIMO信道上的优越性。