Selective Decode-and-Forward Relaying Scheme for Multi-Hop Diversity Transmission Systems
Bibliographic record
Abstract
A selective decode-and-forward relaying protocol for serial multi-hop diversity schemes, which adapts transmissions at the source and relays based on the instantaneous received signal-to-noise ratio at each relay, is developed and analyzed. Based on the proposed selective protocol, if the received signal- to-noise ratio at each relay exceeds a certain threshold, that relay combines, decodes, and re-encodes its received signals and then re-transmits. Otherwise, the source repeats its signal. It is shown that employing the proposed method significantly improves the system performance by achieving diversity order equal to the number of hops while maintaining the same maximum normalized spectral efficiency compared to a multi-hop transmission system employing a fixed decode-and-forward relaying scheme. An exact closed-form expression for calculating the outage probability of a serial multi-hop diversity scheme employing fixed decode-and-forward relaying strategy is also obtained. A rigorous mathematical analysis showing that the serial multi-hop diversity scheme offers no diversity gain is given.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".