Cell signaling error control for reliable molecular communications

Molecular communication (MC) allows implantable devices to communicate using biological data-transmission principles (e.g., molecules as information carriers). However, MC faces significant challenges due to molecular noise, which leads to increased communication errors. Thus, error control techniques become critical for reliable intra-body networks. The noise management and error control in these networks must be based on the characterization of the environment dynamics, i.e., characteristics that increase noise, such as the stochastic behavior of the intercellular channels and the presence of pathologies that affect communication. This work proposes an adaptive error control technique for cell signaling–based MC channels (CELLECs). Using an information-theoretic approach, CELLEC mitigates errors in cellular channels with varying noise conditions. The characteristics of the cellular environment and different noise sources are modeled to evaluate the proposal. The additive white Gaussian tissue noise (AWGTN) produced by stochastic chemical reactions is theorized for healthy cells. The MC model also considers the noise of cells affected by one pathology that disrupts cells’ molecular equilibrium and causes them to become reactive (i.e., Alzheimer’s disease). Analyses show that reactive cells have a higher signal-to-noise ratio (21.4%) and path loss (33.05%) than healthy cells, highlighting the need for an adaptive technique to deal with cellular environment variability. Results show that CELLEC improves communication channel performance by lowering the bit error rate (18%).