Diversity-multiplexing trade-off of the hybrid non-orthogonal amplify-decode and forward protocol
Bibliographic record
Abstract
We propose a hybrid non-orthogonal amplify- decode and forward (NADF) transmission protocol for two half- duplex relay nodes. This strategy allows simple amplify and forward (AF) nodes and more complex decode and forward (DF) nodes to participate jointly in the transmission of information. Such a strategy is useful in networks with heterogeneous devices. Analysis of the diversity-multiplexing trade-off (DMT) shows our protocol to be better than the dynamic decode and forward (DDF) protocol for rates between 1/2 and 2/3. Our technique demonstrates that the DDF protocol is not an upper bound and that protocols exist which perform closer to the DMT limit. The NADF protocol has equal performance to the DDF protocol for rates between 2/3 and one. It has a DMT performance below the DDF protocol and identical to or better than the slotted amplify and forward (SAF) protocol and non-orthogonal amplify and forward (NAF) schemes for rates from zero to 1/2.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".