Channel Modeling for Molecular Communication With Heterogeneous Circular/Spherical Boundary
Bibliographic record
Abstract
Geometry is a key factor in channel modeling for molecular communication (MC), especially when considering its potential for enabling intrabody networks and healthcare applications. Driven by the complex geometries within biological entities, this paper proposes modeling the channel for an MC via diffusion (MCvD) system in bounded circular and spherical environments with a heterogeneous boundary. Specifically, the boundary comprises fully reflecting and absorbing portions, with properties that depend on the presence of absorbing receptors (APs). Moreover, the characteristics of the APs, such as their number, size, and spatial distribution, are variable to better align with realistic boundary conditions. To obtain an accurate channel impulse response (CIR), we employ the homogenization technique to convert the mixed Dirichlet-Neumann boundary into a Robin boundary. Accordingly, we derive a valid CIR expression for the bounded MCvD system, accommodating confined spaces with APs of arbitrary sizes, numbers, and locations. Numerical results based on particle-based simulations validate our analysis. Finally, we investigate the error performance of the MCvD system under various boundary conditions. Simulation results show that a heterogeneous boundary with appropriate parameters has the potential to achieve pulse shaping of the CIR and enhance the performance of point-to-point MCvD systems in both 2D and 3D environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".