Low-Complexity Optical Distribution of Gb/s BPSK UWB Signals
Bibliographic record
Abstract
Optical transport of ultra-wideband (UWB) signals extends the reach of these power-limited signals to several kilometers. We propose and experimentally demonstrate a simple and low-cost optical method to generate UWB pulses. We use few optical components (source/modulator/photodetector), in contrast to most other optical generation techniques. UWB pulses complying with the U.S. Federal Communications Commission spectral mask are generated by modulating the intensity of a continuous-wave laser with a combined signal consisting of the data signal and a sinusoidal signal. For impulse radio UWB, binary phase-shift-keying is accomplished simply by adjusting the amplitudes of the data and the sinusoidal signal. Wireless propagation of the UWB impulses is investigated experimentally at a very high bit rate. The receiver is implemented using a real-time oscilloscope to capture the received waveforms followed by offline signal processing. In particular, we consider a minimum-mean-square error equalizer to counter the multipath-induced intersymbol interference encountered at 1.75 Gb/s. Equalization brings the bit-error-rate within the forward-error correction limit of after 2.5 m of wireless propagation at 1.75 Gb/s.
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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 | 0.000 |
| 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) | 0.003 | 0.001 |
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".