Geometrical-Empirical Channel Propagation Model for Human Presence at 60 GHz
Bibliographic record
Abstract
Previous efforts to develop simulation and/or measurement-based channel propagation models for the effect of human blockage on millimeter-wave communication systems have yielded important results, but lack either accuracy, generality, or simplicity. To fill that void, in this paper we propose a hybrid geometrical-empirical model for human presence; we refer to it as human presence because reflection from the body before and after blockage occurs in addition to diffraction around the body during blockage (as in previous efforts) is incorporated. Specifically, propagation is modeled as the superposition of the main transmission path and reflected and/or diffracted paths from the body; the geometrical component of the model accounts for the phase of each path while the empirical component accounts for its amplitude. To validate the proposed model and extract its empirical parameters, an exhaustive measurement campaign with 120 blockage scenarios, comprising varying human subjects and transmitter-human-receiver configurations, was conducted; a total of 180,000 channel acquisitions was recorded with our precision, state-of the-art 60-GHz channel sounder. The overall model is shown to be computationally efficient yet general enough to accurately represent a wide range of scenarios.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".