Layered Semantic Communication System for Dynamic Scenarios

The 6G wireless communication demands intelligent and versatile interaction between humans and machines that can deal with various intelligent tasks. Semantic communication that focuses on transmitting the meanings rather than the data is expected to be one of the promising technologies to achieve this goal. However, most existing semantic communication systems optimize the whole system under a single objective, lacking the scalabi-lity to dynamic scenarios. For a dynamic scenario with changing channel conditions and background knowledge, we propose a layered semantic communication system (LSCS), which takes advantage of layered coding architec-ture at the semantic and syntactic levels. In addition, a symbolic attention-based denoising network is designed at the receiver to recover transmitted meanings. Simulation results demonstrate that the proposed LSCS can adapt to dynamic scenarios and achieve superior performance over benchmarks under different channel conditions, especially in the low signal-to-noise ratio (SNR) region.