Modeling Molecular Communications with Semantic Communication Theory

Conventional molecular communication systems focus on physical layer aspects mainly: channel coding or modulation schemes, where the type of source signal and meaning are not considered. Modeling molecular communications using semantic communication theory is an emerging area that integrates bio-inspired communication systems with intelligent meaning-aware frameworks. Modeling molecular communications with semantic communication theory involves integrating the physical propagation of molecules with the transmission of meaningful information. This hybrid approach focuses on optimizing communication efficiency by prioritizing the semantic intent of messages rather than raw molecular signal fidelity. We present a simulation scenario for diffusion-based molecular communication with semantic encoding, noise, and the use of a deep neural network as a decoding and classifier of semantic messages.