3-Dimensional Interference Modeling for Cellular Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Planning and optimizing the radio access layer of cellular networks always requires an accurate modeling or measurement of the interference patterns in the network, for almost all technologies. Traditionally, this analysis has been performed using 2-dimensional traffic forecasts, and measurements or propagation predictions performed at ground level. While this applies quite well in a non-urban environment, such an approach is very limited in city centers with many high- rise buildings, where interference affects a very large proportion of traffic above the ground level. We propose a new approach based on 3D modeling of an entire city, for both traffic and propagation data. This new approach, which optimally models in-building traffic and interference in a large-scale network, has been applied to the generation of a 3D interference matrix in Manhattan. We show how this 3D interference matrix can lead to optimal frequency planning, hence improved network performance, of a real TDMA-FDMA network.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 it