Joint localization and channel estimation in flow-assisted molecular communication systems

In this paper, we present a joint localization and channel parameter estimation method in the presence of signal-dependent noise and inter-symbol interference for diffusive molecular communication systems. The joint parameter estimation of the nanomachine can provide reliable communication in a generic diffusive molecular communication system. In particular, an iterative maximum likelihood estimation (MLE) approach for jointly estimating locations, flow velocity, and diffusion coefficient is carried out. The Cramer–Rao lower bound on the variance of channel parameters and location is derived. The normalized estimation error is marginally higher for unknown parameters case than that of some known parameters. The individual result (location estimation or channel parameters estimation) outperforms the existing methods.