Relayer selection strategies in cellular networks with peer-to-peer relaying
Why this work is in the frame
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Bibliographic record
Abstract
We consider a TDMA cellular multihop network where relaying - via wireless terminals that have a good communication link to the base station - is used as a coverage enhancement technique. Provided that the subscriber density is not very low, relaying via wireless terminals can have a significant impact on coverage, capacity, and throughput. This is mainly due to the fact that the signals only have to travel through shorter distances and/or improved paths. In this work, we investigated the effects of relaying node selection strategies (essentially a routing issue) and maximum relayer transmit power level on coverage. Our simulation results show that with a very modest level of relaying node transmit power and with some moderate intelligence incorporated in the relaying node selection scheme, the (high data rate) coverage can be improved significantly through two-hop relaying without consuming any additional bandwidth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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