Gaussian Broadcast Channels with Bidirectional Conferencing Decoders and Correlated Noises
Bibliographic record
Abstract
The two-user Gaussian broadcast channel (BC) with correlated noises and with decoders connected by cooperative links of finite capacities (known as conferencing decoders) is considered. A novel outer bound on the capacity region is established. For the channel with fully correlated noises (i.e., the noise correlation is either 1 or -1), the new outer bound yields exact capacity region for two cases: 1) BCs with degraded message sets; 2) BCs with one-sided conferencing from the weaker receiver to the stronger receiver. For these two cases, it is also shown that the outer bound is within half bits to the capacity region for arbitrary noise correlation. Furthermore, for the Gaussian BC with arbitrary noise correlation λ, we show that regardless of the capacities of conferencing links, a one-sided cooperative scheme (from the stronger user to the weaker one) based on decode-and-forward is sufficient to achieve the capacity region to within $\frac{1}{2}\log \left( {\frac{2}{{1 - |\lambda |}}} \right)$ bits.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".