Novel Rateless Coded Selection Cooperation in Dual-Hop Relaying Systems
Bibliographic record
Abstract
Selection cooperation is proposed for rateless coded relaying by developing a novel low-complexity protocol that exploits all source-destination, source-relay, and relay-destination link qualities for relay selection. The source or any decoding relay having a link to the destination with a gain greater than a preset threshold is a candidate for collaboration. When the number of candidates reaches a preset value, the best of them is selected for passing the source data to the destination. The source and relays are informed of the selected node by a broadcast feedback from the destination. Limited feedback is required only between the destination and the other nodes and merely for declaring success in decoding or selecting the next transmitting node. The system power and complexity are independent of the system parameters. Also, the system dispenses with internode synchronization at carrier or symbol levels, multireception combining, multiaccess interference, and multiuser detection. Assuming independent fading on different links, a general performance analysis of the new system is presented valid for any individual link fading model. It is shown through numerical results that the novel scheme is considerably more energy efficient, for diverse input conditions, than a more complex commensurate scheme previously proposed. Also, the energy efficiency is enhanced as the number of relays increases, such that despite an increase in the capacity, the energy expenditure diminishes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".