Performance Analysis of RIS-Aided Communications based on Student-T Copula
Bibliographic record
Abstract
Reconfigurable intelligent surface (RIS) has received remarkable attention for its potential to improve the capacity and coverage of wireless communication networks. In this paper, we evaluate the performance of RIS-assisted communication systems in the presence of phase noise with the help of Student-T copula in two scenarios. The first one is the cascade link or RIS link and the second scenario involves direct link in conjunction with cascade link. In particular, we first analyze the probability density function and the cumulative distribution function of the signal-to-noise-ratio with/without direct link. Then, we investigate the outage probability and ergodic capacity of the RIS-assisted network by using Student- T copula function to characterize the non-linear dependency among the signal components. Furthermore, we reveal the relation between the Student- T copula dependency parameter and Pearson correlation coefficient. Finally, numerical results are presented confirm the validity of the analytical closed-form expressions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".