Filters for ISI Suppression in Molecular Communication via Diffusion

TL;DR

This paper introduces a novel filter-based approach for suppressing inter-symbol interference in molecular communication via diffusion, improving signal recovery in noisy, high-ISI environments without estimating ISI.

Contribution

It proposes a new filter design principle for ISI suppression in MCvD, along with a signal detection scheme that outperforms existing methods in high-ISI and noisy conditions.

Findings

Proposed filter effectively suppresses ISI and noise.

Outperforms state-of-the-art ISI-suppression methods.

Enables reliable signal detection in challenging environments.

Abstract

Molecular communication via diffusion (MCvD) is considered as one of the most feasible communication paradigms for nanonetworks, especially for bio-nanonetworks which are usually in water-rich biological environments. Two effects that deteriorates the signal in MCvD are noise and inter-symbol interference (ISI). The expected channel impulse response of MCvD has a long and slow attenuating tail due to molecular diffusion which causes ISI and further limits the slow data rate of MCvD. The extent that ISI and noise are suppressed in an MCvD system determines its effectiveness, especially at a high data rate. Although ISI-suppression approaches have been investigated, most of them are addressed as non-essential parts in other topics, such as signal detection or modulation. Furthermore, most of the state-of-the-art ISI-suppression approaches are performed by subtracting the estimated ISI from the total signal. In this work, we investigate ISI-suppression from a new perspective of filters to filter ISI out without any ISI estimation. The principles for a good design of ISI-suppression filters in MCvD are investigated. Based on the principles, an ISI-suppression filter with good anti-noise capability and an associated signal detection scheme is proposed for MCvD scenarios with both ISI and noise. We compare the proposed scheme with the state-of-the-art ISI-suppression approaches. The result manifests that the proposed ISI-suppression scheme could recover signals deteriorated severely by both ISI and noise, which could not be effectively detected by the state-of-the-art ISI-suppression approaches.