Asymptotic Outage Probability for Amplify-and-Forward CDMA Systems over Nakagami-m Fading Channels
Bibliographic record
Abstract
In this paper, we address the performance of cooperative code-division multiple-access (CDMA) systems using amplify-and-forward (AF) relaying over independent nonidentical (i.ni.d) Nakagami-m fading channels. The outage probability of the system is investigated using the moment generating function (MGF) of the total signal-to-noise ratio (SNR) at the base station. Since it is complicated to derive a closed form expression of the outage probability, we derive an approximation for the probability density function (PDF) of the total SNR which in turn enables us to derive the asymptomatic outage probability for any value of the fading parameter m. Simulation results are presented to assess the accuracy of our analytical results. Furthermore, using the derived outage probability, we investigate the diversity advantage of the cooperative system under different system settings.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".