Semi-Blind Channel Estimation for Diffusive Molecular Communication

In this letter, we consider the problem of channel estimation for diffusive molecular communication (MC) systems. The presence of memory in diffusive MC channels, along with channel noise caused by various sources, necessitate the development of accurate channel estimators to acquire the channel impulse response (CIR). Previous works proposed pilot-based estimators based on the maximum likelihood (ML) and least squares (LS) criteria. In contrast, we propose three novel semi-blind estimators, one based on the expectation maximization (EM) framework and two based on the decision-directed (DD) estimation strategy. We also obtain the corresponding semi-blind Cramer-Rao bound (CRB). Our simulation results show that all the proposed semi-blind estimators offer substantially lower mean-squared error than the existing pilot-based estimators. The EM estimator provides the highest accuracy and converges to the semi-blind CRB, while the DD estimators offer convenient low-complexity alternatives. Importantly, the proposed estimators allow for a significant reduction in the number of transmitted pilots, without compromising the estimation accuracy.