Improved Expression for Intensity Noise in Multimedia over Fiber Networks
Bibliographic record
Abstract
The relative intensity noise (RIN) plays an important role in multimedia over fiber (MOF) networks. The RIN is conventionally considered to be proportional to the square of the mean optical power. This is true under small signal, single channel conditions. Nevertheless, experiments have shown that the RIN also increases with the modulation index m that reflects the power of the stochastic modulating signal s(t). Winston Way observed this dependency and mentioned a dynamic RIN under direct modulation conditions. Accurate characterization of the RIN is important especially in MOF systems that support multiple radio channels in subcarrier multiplexed manner in addition to digital data. Modern MOF links tend to have large carrier to sideband ratio that enhances RIN. In this paper, a mathematical expression for the RIN is derived from fundamental principles that shows the dependency of RIN on modulation index m and modulating multimedia signal power E[s2(t)]. The new expression better explains the excess increment of noise power in MOF systems observed many authors
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".