Capacity Limits of Diffusion-Based Molecular Timing Channels

TL;DR

This paper establishes capacity bounds for diffusion-based molecular timing channels, analyzing how particle release timing and detection methods influence information capacity, with results showing capacity can grow significantly with particle diversity and delay control.

Contribution

It introduces capacity limits for molecular timing channels, deriving bounds for different detection models and showing how delay control and particle diversity enhance capacity.

Findings

Capacity bounds are tight for single-particle release.

Capacity increases poly-logarithmically with the number of particles.

Diversity in particle paths significantly boosts achievable data rates.

Abstract

This work introduces capacity limits for molecular timing (MT) channels, where information is modulated in the release timing of small information particles, and decoded from the time of arrivals at the receiver. It is shown that the random time of arrival can be represented as an additive noise channel, and for the diffusion-based MT (DBMT) channel this noise is distributed according to the L\'evy distribution. Lower and upper bounds on the capacity of the DBMT channel are derived for the case where the delay associated with the propagation of the information particles in the channel is finite, namely, when the information particles dissipate after a finite time interval. For the case where a single particle is released per channel use, these bounds are shown to be tight. When the transmitter simultaneously releases a large number of particles, the detector at the receiver may not be able to precisely detect the arrival time of all the particles. Therefore, two alternative models are considered: detection based on the particle that arrives first, or detection based on the average arrival times. Tight lower and upper bounds are derived for these two models. It is shown that by controlling the maximal delay of the information particles, the capacity can increase poly-logarithmically with the number of released particles. As each particle takes a random independent path, this diversity of paths is analogous to receiver diversity and can be used to considerably increase the achievable data rates.