Design and Analysis of Wireless Communication Systems Using Diffusion-Based Molecular Communication Among Bacteria

TL;DR

This paper explores the design and analysis of biologically-inspired wireless communication systems using bacteria, focusing on molecular diffusion, quorum sensing, and information transfer limits in bacterial networks.

Contribution

It introduces a model for reliable bio nodes formed by bacterial populations and analyzes their communication capabilities and theoretical limits.

Findings

Derived the capacity limits of bacterial molecular communication channels.

Analyzed the performance of M-ary signaling schemes in bacterial networks.

Quantified error probabilities for different molecular communication strategies.

Abstract

The design of biologically-inspired wireless communication systems using bacteria as the basic element of the system is initially motivated by a phenomenon called \emph{Quorum Sensing}. Due to high randomness in the individual behavior of a bacterium, reliable communication between two bacteria is almost impossible. Therefore, we have recently proposed that a population of bacteria in a cluster is considered as a bio node in the network capable of molecular transmission and reception. This proposition enables us to form a reliable bio node out of many unreliable bacteria. In this paper, we study the communication between two nodes in such a network where information is encoded in the concentration of molecules by the transmitter. The molecules produced by the bacteria in the transmitter node propagate through the diffusion channel. Then, the concentration of molecules is sensed by the bacteria population in the receiver node which would decode the information and output light or fluorescent as a result. The uncertainty in the communication is caused by all three components of communication, i.e., transmission, propagation and reception. We study the theoretical limits of the information transfer rate in the presence of such uncertainties. Finally, we consider M-ary signaling schemes and study their achievable rates and corresponding error probabilities.