Robust power control of single sink optical networks with time-delays
Bibliographic record
Abstract
We study the stability of game-theoretic based power control algorithms on multi-link optical networks in the presence of time-delays and uncertainties. The control algorithms, originally developed in the absence of time-delays and uncertainties, adjust the signal powers at the transmitters to solve the optical signal-to-noise ratio (OSNR) optimization problem. This minimizes the bit error rate of the signal channels. We apply the game-theoretic framework to a perturbed OSNR model in the presence of time-delays. Uncertainties in the OSNR model appear as norm-bounded uncertainties in the noise powers, system gains, and channel powers. The time-delays are due to signal propagation between the channel sources and OSNR output. We restrict our analysis to single sink network topologies. A primal-dual control scheme ensures convergence to the Nash equilibrium, and OSNR optimization. The resultant closed-loop system has two time-scales. Robust stability in the presence of time-delays is established via singular perturbation theory modified for Lyapunov-Krasovskii theory.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".