Perspectives of Geometry Based Deterministic Reference Channel Models for 5G Applications
Bibliographic record
Abstract
Geometry based reference channel models (GBRCM) have been one of key topics of radio channel modelling for years. Their development and applications have been bringing the academy, industry and standardization bodies together in several large projects, such are 3GPP, WINNER, METIS, etc. With 5G as an ongoing process, it is important to continue and adapt GBRCM research to new arriving technologies and applications. This paper discusses perspectives of geometry based deterministic reference channel models (GBDRCM), a subset of GBRCM, for 5G reference channel models, focusing on some key concepts of 5G: massive MIMO, Internet of Things and resources. The main hypothesis lies on the concept of deterministic reference channel models as an alternative for the commonly accepted stochastically based geometry based RCMs. The proposed solution is based on the concept of ray entity delivered from ray tracing simulations.
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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 | 0.000 | 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 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".