WLC33-2: On Relaying in Cooperative Static Channels
Bibliographic record
Abstract
It is shown that regenerative relaying in a dual- hop diversity static or quasi-static relay channel can outperform non-regenerative relaying only if the source-relay link is reliable and power allocation to the source and the relay is optimized. In regenerative relaying, a maximal ratio combining receiver at the destination has an error floor at high signal-to-noise ratios. However, maximal ratio combining is not a maximum-likelihood structure in this application. Maximum-likelihood detection at the destination can remove this error floor, but cannot always make the performance of regenerative relaying surpass that of non- regenerative relaying. A hybrid protocol which avoids some of the limitations of previous relaying schemes is proposed. Conditions under which relaying increases the equivalent source-destination signal-to-noise ratio, and hence, the source-destination channel capacity are derived and the gain of the cooperation is calculated. The analysis provides quantitative measures for choosing the best relay among a set of candidates.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".