Exact Closed-Form Expressions for the Outage Probability and Ergodic Capacity of Decode-and-Forward Opportunistic Relaying
Bibliographic record
Abstract
Exact statistics of the local signal-to-noise ratios (SNRs) of the best relay in decode-and-forward (DF) opportunistic relaying (ORe) are derived. It is observed that although the different links are assumed to suffer independent fadings, the best-relay local SNRs are dependent. Both joint and marginal statistics are determined for the general case of nonidentical SNR distributions, and a source-relay-symmetric (S-R-sym.), relay-destination-symmetric (R-D-sym.) case. Both general fading and Rayleigh fading cases are considered. Using the statistics derived, exact, closed-form expressions for the outage probability and ergodic capacity of DF ORe are calculated in the S-R-sym., RD-sym., Rayleigh fading case. The exact results for the outage probability show almost linearly increasing diversity order with the number of relays. The exact results for the ergodic capacity show a multiplexing gain almost equaling one half and a power gain increasing with the number of relays that exhibits diminishing returns.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".