Wavelength Reuse in a UWB Over WDM-PON Based on Injection Locking of a Fabry–Pérot Laser Diode and Polarization Multiplexing
Bibliographic record
Abstract
Wavelength reuse in a symmetric ultra-wideband (UWB) over wavelength-division-multiplexing passive optical network based on injection locking of a Fabry-Pérot laser diode (FP-LD) and polarization multiplexing is proposed and experimentally demonstrated. In the proposed scheme, the downstream UWB signal and baseband signal are generated and polarization multiplexed in the central station and sent to a base station (BS) over an optical fiber. At the BS, one of the downstream signals is selected to injection lock the FP-LD. It is demonstrated theoretically and experimentally that the upstream service performance is less sensitive to the modulation depth of the downstream UWB signal than the baseband signal, and the use of the downstream UWB signal as the injection signal would contribute to a better transmission performance for both the downstream and upstream services. Thus, the downstream UWB signal is selected as the injection signal. An experiment is performed. When the FP-LD is injection locked by a downstream UWB signal, a clear optical carrier is generated which is reused for upstream UWB and baseband transmission. A bidirectional point-to-point transmission of 1.25 Gb/s UWB signal and 10 Gb/s baseband signal over 25-km single-mode fiber using a single wavelength is demonstrated. The bit error rate performances and the eye diagrams for both downstream and upstream transmissions are measured.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".