Bibliographic record
Abstract
This paper presents a method to model and simulate time-varying narrowband multiple-input-multiple-out (MIMO) channels based on observations from measured data. The data were obtained in a vehicular urban environment, with a fixed transmitter array and a mobile receiver array. The measured channel response matrices were decomposed to isolate the coupling from the transmitter eigenbasis to the received eigenbasis, as in the Weichselberger model. These complex coupling elements have been characterized and seen to comprise directional components that may be Ricean or Rayleigh fading. The Rayleigh fading directional components can be well modeled using the von Mises probability density function, which is parameterized for the time-varying model using the measured data. The model has been validated by comparing the mutual information and eigenstructure autocorrelation characteristics of its output with those of the measured data. The statistical nature of the model means that different realizations can be generated, each representative of the originating data.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".