Millimeter-Wave and UWB Over a Colorless WDM-PON Based on Polarization Multiplexing Using a Polarization Modulator
Bibliographic record
Abstract
A broadband millimeter-wave (mmW) at 60-GHz band and an impulse radio ultra-wideband (IR-UWB) over a colorless 100-GHz dense wavelength division multiplexing (DWDM) passive optical network (PON) that supports simultaneous transmission of a broadband mmW signal, a UWB signal and a wireline baseband signal is experimentally demonstrated. At the transmitter, a polarization modulator (PolM) is employed, which operates in conjunction with a polarization controller (PC) and a polarization beam splitter (PBS) as an equivalent Mach-Zehnder modulator (MZM). For 60-GHz and IR-UWB signal transmission, the equivalent MZM is biased at the minimum transmission point to generate two sidebands that are separated at a frequency in the 60-GHz band, and the wireless signals (60 GHz and IR-UWB) are carried by the two sidebands. For the wireline baseband transmission, the equivalent MZM is biased at the maximum transmission point to generate only the optical carrier, and the wireline signal is carried by the optical carrier. The wireline signal and the wireless signals are orthogonally polarized and sent over a single-mode fiber (SMF) to a base station (BS). For each WDM channel in the central station (CS) and the BS, since no optical filters are employed, colorless operation is supported. Point-to-point error-free transmission of a 1.25-Gbps mmW signal, a 1.25-Gbps IR-UWB signal and a 10-Gbps wireline signal over a 25-km SMF is experimentally demonstrated. The number of users that can be supported by the proposed colorless WDM-PON is estimated based on the measured receiver sensitivities.
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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".