# Channel Sensing in Molecular Communications with Single Type of Ligand Receptors

## TL;DR

This paper introduces a novel method for molecular channel sensing using a single receptor type to estimate multiple ligand concentrations simultaneously, enabling interference reduction and multi-user communication in nanonetworks.

## Contribution

It develops channel sensing techniques based on receptor binding times, derives the CRLB for multi-ligand estimation, and proposes practical estimators and synthetic receptor designs.

## Key findings

- Efficient estimation of up to 10 ligand types with NMSE below 10^{-2}
- Derivation of the CRLB for multi-ligand concentration estimation
- Design of synthetic receptors using modified kinetic proofreading and CRNs

## Abstract

Molecular Communications (MC) uses molecules as information carriers between nanomachines. MC channel in practice can be crowded with different types of molecules, i.e., ligands, which can have similar binding properties causing severe cross-talk on ligand receptors. Simultaneous sensing of multiple ligand types provides opportunities for eliminating interference of external molecular sources and multi-user interference (MUI), and developing new multiple access techniques for MC nanonetworks. In this paper, we investigate channel sensing methods that use only a single type of receptors and exploit the amount of time receptors stay bound and unbound during ligand-receptor binding reaction to concurrently estimate the concentration of multiple types of ligands. We derive the Cram\'er-Rao Lower Bound (CRLB) for multi-ligand estimation, and propose practical and low-complexity suboptimal estimators for channel sensing. We analyze the performance of the proposed methods in terms of normalized mean squared error (NMSE), and show that they can efficiently estimate the concentration of ligands up to $10$ different types with an average NMSE far below $10^{-2}$. Lastly, we propose a synthetic receptor design based on modified kinetic proofreading (KPR) scheme to sample the unbound and bound time durations, and a Chemical Reaction Network (CRN) to perform the required computations in synthetic cells.