Molecular ISAC via Markov State-Space Modeling: Joint Distance Sensing and Data Detection

2026-05-03

AI Summary

This work addresses the challenge of simultaneously achieving high-precision distance estimation and reliable data detection in microfluidic molecular communication using a single molecular observation. It pioneers the introduction of Integrated Sensing and Communication (ISAC) concepts into this domain by constructing a distance-parameterized Markovian state-space model that jointly characterizes the channel impulse response and the block observation structure of on-off keying signals. A low-complexity receiver is designed through pilot-assisted initialization, decision-feedback equalization, and iterative optimization. This approach enables mutual performance gains between distance estimation and symbol detection under a unified observation framework, significantly enhancing ranging accuracy and reducing bit error rates, thereby demonstrating the feasibility and superiority of molecular ISAC on microfluidic platforms.

Abstract

This paper develops a molecular integrated sensing and communication (ISAC) framework that exploits the same molecular observations for physical-parameter sensing and data detection. As a representative instantiation, we consider a microfluidic molecular communication (MC) channel and study transmitter--receiver (TX--RX) distance sensing, where the distance affects the propagation delay, transient response, and inter-symbol interference structure. A distance-parameterized Markov state--space model is established to obtain distance-dependent channel impulse responses and a block observation model for on-off keying signaling. Based on this model, we design a pilot-assisted low-complexity receiver that combines distance initialization, decision-feedback equalization (DFE), and iterative joint refinement. Numerical results show accurate distance sensing and improved bit error ratio (BER), demonstrating the mutual benefit between sensing and communication and highlighting microfluidic MC as a representative platform for molecular ISAC.

Problem

• Molecular ISAC
• Distance Sensing
• Data Detection
• Molecular Communication
• Microfluidic Channel

Innovation

• Molecular ISAC
• Markov state-space modeling
• distance sensing
• decision-feedback equalization
• microfluidic molecular communication