# Channel Estimation for Diffusive MIMO Molecular Communications

## TL;DR

This paper develops and compares channel estimation techniques for diffusive MIMO molecular communication systems, aiming to improve data rates by accurately estimating the channel impulse response despite severe ISI.

## Contribution

It introduces training-based CIR estimation methods for D-MIMO channels, deriving maximum likelihood and least-squares estimators, and designs training sequences to optimize estimation accuracy.

## Key findings

- Maximum likelihood and least-squares estimators derived
- Training sequences designed to minimize Cramér-Rao bound
- Sub-optimal estimators validated against theoretical bounds

## Abstract

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.