AF Cooperative CDMA Outage Probability Analysis in Nakagami-$m$ Fading Channels
Bibliographic record
Abstract
The performance of amplify-and-forward (AF) cooperative code-division multiple-access (CDMA) systems is analyzed over independent nonidentical (i.n.i.) Nakagami-mfading channels. In the underlying AF relaying scheme, each relay applies interference suppression to the received signal to mitigate the effect of multiple-access interference (MAI) where a soft estimate is obtained before signal amplification takes place. The outage probability of the system is analyzed using the cumulative distribution function (cdf) of the total signal-to-noise ratio (SNR) at the base station. In that, we derive a simplified yet tight lower bound for the AF relaying system. We also define an approximation for the probability density function (pdf) of the total SNR, which enables us to derive an asymptotic outage probability of the system. The derived asymptotic outage probability is used to evaluate the achievable diversity order for various system parameters. Simulations are presented to verify the accuracy of our analytical results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| 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 | 0.001 |
| 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".