  In diffusion-based communication, as for molecular systems, the achievable
data rate is very low due to the slow nature of diffusion and the existence of
severe inter-symbol interference (ISI). Multiple-input multiple-output (MIMO)
technique can be used to improve the data rate. Knowledge of channel impulse
response (CIR) is essential for equalization and detection in MIMO systems.
This paper presents a training-based CIR estimation for diffusive MIMO (D-MIMO)
channels. Maximum likelihood and least-squares estimators are derived, and the
training sequences are designed to minimize the corresponding Cram\'er-Rao
bound. Sub-optimal estimators are compared to Cram\'er-Rao bound to validate
their performance.
