Optimal resource sharing and network beamforming for bidirectional relay networks
Bibliographic record
Abstract
We present a resource sharing scheme where two transceiver pairs share their resources in a collaborative manner. The two transceivers in each pair wish to communicate bidirectionally through several distributed relays. We assume that one of the pairs is the primary pair, meaning that it owns radio frequency spectrum resources and needs to be serviced with a minimum guaranteed rate. The other pair, called the secondary pair, is assumed to own the relay infrastructure. The secondary network allows the primary pair to use the relays in order to establish a bidirectional communication between its transceivers. In exchange for this cooperation, the primary pair assigns a portion of its spectral resources to the secondary pair, for setting up a two-way communication between the secondary transceivers. Assuming amplify-and-forward relaying scheme, the relays collectively build two network beamformers, each of which enables communication between the two transceivers in one pair. To optimally calculate the primary and secondary network parameters, we propose a max-min optimization problem which is amenable to a simple line search based solution with a low computational complexity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".