Performance analysis of a 400-Gbps DWDM-FSO system using advanced modulation formats and under adverse weather conditions
Bibliographic record
Abstract
Free space optical (FSO) systems offer an attractive and cost-effective solution for providing communication services in remote regions, as they allow secure transmission without the need for licensing and with lower deployment costs. However, the performance of FSO systems can be significantly impacted by atmospheric turbulences, creating considerable challenges to their deployment. To meet the expanding bandwidth requirements in optical networks, dense wavelength division multiplexing (DWDM) has emerged as a viable option. The development of a 400-Gbps DWDM-FSO system with advanced modulation formats is the subject of this paper. To ensure efficient energy conservation in such a system, power consumption needs to be minimized while maintaining performance level; this calls for optimization of different components within the system. The system is made up of 10 channels and each channel can transmit data at 40 Gbps. Various modulation schemes like carrier-suppressed return-to-zero, modified duo binary return-to-zero, differential phase shift keying, and duo binary return-to-zero are studied for their impact on system performance parameters Q-factor and bit error rate (BER) in C-band around 1550 nm wavelengths. The assessment is also extended to the effects that changing FSO length, input power, and data rate have on these two parameters as well as an evaluation regarding how differing atmospheric conditions influence the FSO system’s effectiveness.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".