A DoF analysis of compress-and-forward in MIMO Gaussian relay channel with correlated noises
Bibliographic record
Abstract
This paper studies the effectiveness of compress-and-forward (CF) relaying scheme for a multiple-input multiple-output (MIMO) Gaussian relay channel with an out-of-band finite-capacity relay-to-destination link in which noises at the relay and destination are correlated due to common sources of interference. This scenario is motivated by the possibility of using device-to-device links for inter-cell interference mitigation in cellular networks. We characterize the necessary and sufficient conditions on the number of antennas under which the relay link rate can result in a near one-to-one improvement to the overall throughput in the high signal-to-noise-ratio and interference-to-noise-ratio regime. We show that these conditions coincide with the necessary and sufficient condition under which full cooperation between relay and destination can improve the degrees of freedom of the relay channel. Simultaneous diagonalization by *congruence enables this characterization.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 | 0.000 |
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 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".