[Paper Review] Robust Modulation Technique for Diffusion-based Molecular Communication in Nanonetworks

Subodh Pudasaini, Seokjoo Shin+1 more|arXiv (Cornell University)|Jan 16, 2014

Molecular Communication and Nanonetworks2 references16 citations

TL;DR

This paper proposes Zebra-CSK, a robust modulation technique for diffusion-based molecular communication that reduces inter-symbol interference (ISI) by using inhibitor molecules to suppress residual messenger molecules from prior symbols. By selectively suppressing interfering molecules, Zebra-CSK improves channel capacity by up to 37.31% and reduces symbol error probability by 85.61% compared to conventional CSK.

ABSTRACT

Diffusion-based molecular communication over nanonetworks is an emerging communication paradigm that enables nanomachines to communicate by using molecules as the information carrier. For such a communication paradigm, Concentration Shift Keying (CSK) has been considered as one of the most promising techniques for modulating information symbols, owing to its inherent simplicity and practicality. CSK modulated subsequent information symbols, however, may interfere with each other due to the random amount of time that molecules of each modulated symbols take to reach the receiver nanomachine. To alleviate Inter Symbol Interference (ISI) problem associated with CSK, we propose a new modulation technique called Zebra-CSK. The proposed Zebra-CSK adds inhibitor molecules in CSK-modulated molecular signal to selectively suppress ISI causing molecules. Numerical results from our newly developed probabilistic analytical model show that Zebra-CSK not only enhances capacity of the molecular channel but also reduces symbol error probability observed at the receiver nanomachine.

Motivation & Objective

• Address the significant inter-symbol interference (ISI) in diffusion-based molecular communication caused by long-tailed molecular concentration signals.
• Overcome the limitations of Concentration Shift Keying (CSK), which suffers from high symbol error rates due to overlapping molecular signals from previous symbols.
• Design a robust modulation scheme that enhances reliability and spectral efficiency in nanonetworks without increasing transmitter or receiver complexity unduly.
• Demonstrate that inhibitor molecules can effectively suppress residual messenger molecules, thereby improving detection accuracy at the receiver.

Proposed method

• Introduce two types of molecules: messenger molecules for information encoding and inhibitor molecules for suppressing residual messenger molecules from prior symbols.
• Apply a time-slotted transmission model where binary symbols (0 or 1) are encoded by releasing n molecules at the start of each slot.
• Use inhibitor molecules with a specified inhibition efficiency β to selectively bind and deactivate messenger molecules from previous symbols.
• Develop a probabilistic analytical model to compute the probability of symbol detection at the receiver, incorporating the effects of diffusion, molecular decay, and inhibition.
• Derive expressions for mutual information and symbol error probability based on the joint probability distribution of transmitted and received symbols.
• Optimize the detection threshold λ to maximize mutual information and minimize symbol error rate under varying inhibition efficiencies (β = 0, 0.5, 1).

Experimental results

Research questions

• RQ1 How does the use of inhibitor molecules affect inter-symbol interference (ISI) in diffusion-based molecular communication?
• RQ2 To what extent can Zebra-CSK improve channel capacity compared to conventional CSK?
• RQ3 What is the minimum achievable symbol error probability of Zebra-CSK, and how does it compare to CSK under optimal detection thresholds?
• RQ4 How does the distance between transmitter and receiver nanomachines affect the performance gain of Zebra-CSK over CSK?
• RQ5 How does the inhibition efficiency β of the inhibitor molecules influence the symbol error probability and mutual information in the system?

Key findings

• Zebra-CSK increases channel capacity by 29.85% and 37.31% compared to conventional CSK when inhibition efficiency β is 0.5 and 1.0, respectively.
• The minimum symbol error probability of Zebra-CSK is 0.017 (β = 0.5) and 0.00993 (β = 1.0), representing a 75.36% and 85.61% reduction compared to CSK’s minimum error probability of 0.069.
• The mutual information between transmitted and received symbols peaks at a detection threshold lower than the optimum for CSK, indicating improved information transfer efficiency.
• Symbol error probability in Zebra-CSK is consistently lower than in CSK across all tested distances between transmitter and receiver nanomachines.
• The performance gain of Zebra-CSK over CSK in terms of symbol error probability increases with greater distance between transmitter and receiver, especially for moderate to high inhibition efficiencies.
• The proposed model confirms that inhibitor molecules with β = 1.0 (perfect inhibition) yield the highest performance improvement, validating the effectiveness of targeted ISI suppression.