Markov State--Space Modeling and Channel Characterization for DNA-Based Molecular Communication
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914418732826624 |
|---|---|
| author | Zheng, Ruifeng Xu, Zhihan Volkova, Veronika Zhou, Pengjie Schottlender, Martín Cabrera, Juan A. Fitzek, Frank H. P. Hofmann, Pit |
| author_facet | Zheng, Ruifeng Xu, Zhihan Volkova, Veronika Zhou, Pengjie Schottlender, Martín Cabrera, Juan A. Fitzek, Frank H. P. Hofmann, Pit |
| contents | In this paper, we study DNA-based molecular communication with microarray-style reception under reversible hybridization, where the bound-state observation exhibits both inter-symbol interference and colored counting noise. To capture these effects in a communication-oriented form, we develop a Markov state-space framework based on a voxelized reaction--diffusion model, in which a block-structured transition matrix describes molecular transport and binding/unbinding dynamics. For the microarray specialization, this representation yields the channel impulse response, the equilibrium gain, and a settling-time-based characterization of the effective channel memory. Building on the resulting symbol-rate observation model for on--off keying, we derive a grouped-binomial counting model and obtain a closed-form expression for the covariance of the counting noise. Based on these statistics, we further develop a differential-threshold detector and a finite-memory decision-feedback equalizer. Numerical results validate the theoretical correlation behavior and show that the relative performance of the proposed receivers depends strongly on the channel-memory regime. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_23394 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Markov State--Space Modeling and Channel Characterization for DNA-Based Molecular Communication Zheng, Ruifeng Xu, Zhihan Volkova, Veronika Zhou, Pengjie Schottlender, Martín Cabrera, Juan A. Fitzek, Frank H. P. Hofmann, Pit Signal Processing Emerging Technologies In this paper, we study DNA-based molecular communication with microarray-style reception under reversible hybridization, where the bound-state observation exhibits both inter-symbol interference and colored counting noise. To capture these effects in a communication-oriented form, we develop a Markov state-space framework based on a voxelized reaction--diffusion model, in which a block-structured transition matrix describes molecular transport and binding/unbinding dynamics. For the microarray specialization, this representation yields the channel impulse response, the equilibrium gain, and a settling-time-based characterization of the effective channel memory. Building on the resulting symbol-rate observation model for on--off keying, we derive a grouped-binomial counting model and obtain a closed-form expression for the covariance of the counting noise. Based on these statistics, we further develop a differential-threshold detector and a finite-memory decision-feedback equalizer. Numerical results validate the theoretical correlation behavior and show that the relative performance of the proposed receivers depends strongly on the channel-memory regime. |
| title | Markov State--Space Modeling and Channel Characterization for DNA-Based Molecular Communication |
| topic | Signal Processing Emerging Technologies |
| url | https://arxiv.org/abs/2603.23394 |