Signal detection for molecular communication: model-based vs. data-driven methods

Multi-scale molecular communication (MC) employs the characteristics of information molecules for information exchange. The received signal in MC inevitably encounters severe inter-symbol interference and signal-dependent noise due to the stochastic diffusion mechanism. Focusing on the critical signal detection in MC, first this article reviews the commonly used mod-el-based detectors and exposes their limitations in practical implementation. Then the emerging data-driven detectors that can make up for some deficiencies of the model-based detectors are presented. Despite the black-box nature of the data-driven detectors, the explainable artificial intelligence can be further investigated for the performance improvement of transparency and trust. Finally, some open research issues and future research directions in receiver design are discussed.