Bibliographic record
Abstract
Integrating an ultrawideband-over-fiber (UWBoF) system into a wavelength division multiplexing passive optical network (WDM-PON) is of great interest due to the high potential to provide high data-rate and flexible wired and wireless services with a favorable cost. In this paper, we perform a comprehensive study on an impulse radio UWBoF system compatible with the WDM-PON architecture implemented based on a photonic microwave bandpass filter. The bandpass filter is a two-tap delay-line filter implemented using either a polarization modulator (PolM) or a phase modulator (PM), which is used to simultaneously shape an electrical Gaussian-like pulse to an optical UWB pulse and reduce the out-band noise and interference. The features of the photonic microwave bandpass filters are theoretically studied. The photonic microwave bandpass filter based on a PolM would produce a chirp-free UWB signal, while the one based on a PM would generate a UWB signal that is insensitive to fiber dispersion. A single-channel UWBoF system with ON-OFF keying, biphase modulation, and pulse-position modulation without and with time hopping are experimentally studied. The experimental results agree well with the theoretical predictions. A four-channel UWBoF broadcasting network as well as a hybrid WDM-PON network to provide both wireless and wired services is also experimentally investigated. Results show that a conventional WDM-PON network could be easily upgraded to provide UWB services by incorporating the proposed photonic microwave bandpass filter.
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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 | 0.000 |
| 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".