Application of Reflecting Panels in Realisation of Antenna Corridor for Train Communications
Bibliographic record
Abstract
At the advent of 5G mobile communication systems, reliable and fast wireless communications for the user equipments onboard a train is crucial. One of the desirable cost-effective solutions is to use dedicated antennas installed along the train tracks. This is known as so-called antenna corridor. Usually, the antenna corridor solution is used in combination with an antenna on the roof-top of the wagon and a repeater plus one (or few) leaky feeder cables inside the compartment. Nevertheless, for certain reasons, it is more desirable to receive signals into the wagon directly through its window panes. The latter causes extra losses due to the wide (i.e., ≈ 90°) arrival angles between incoming waves and the window panes’ surface vector. In this paper, we propose to use a passive reflector which is installed alongside the railway track to forward the incoming waves towards the wagon. We use a simple 45° slanted plane reflector and quantify the reduction it yields in pathloss between an arbitrary transmit antenna and an ideal dual-port dual-polarised isotropic antenna within a selected wagon.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".