EDFA-Based All-Optical Relaying in Free-Space Optical Systems
Bibliographic record
Abstract
Free-space optical (FSO) communication has recently gained a lot of interest for last-mile terrestrial applications. Some of its advantages include high data rates, ease of deployment, license-free operation, and high security. However, the weather-dependent optical wireless channel introduces attenuation and intensity variations known as scintillation which impose severe challenges for reliable data transmission. The distance dependence of both attenuation and scintillation motivates the use of relays as a means of improving the system performance and extending the range of communication. In this paper, we advocate the use of all-optical relays equipped with erbium-doped fiber amplifiers (EDFAs), which, in contrast to conventional FSO relays with electrical amplification, avoid optical-to-electrical and electrical-to-optical conversions. We develop accurate signal and noise models for fixed and variable gain all-optical and electrical relaying which include the effects of all relevant system parameters and types of noise. For performance evaluation, we analyze the outage probability of all-optical relaying in lognormal fading for dual-hop and multi-hop transmission. Our results show that all-optical relays, while simpler from an implementation point of view, outperform electrical relays unless the number of relays is very large. Moreover, for a fixed source-destination distance, performance improves as the number of hops (relays) increases up to a certain point beyond which adding more hops deteriorates performance.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".