Pulse Shapes That Outperform Traditional UWB Antenna/Waveform Combinations
Bibliographic record
Abstract
Traditionally the Gaussian monocycle pulse and its higher derivatives have been proposed and deployed as impulse radio ultra-wideband (IR-UWB) pulses. Although relatively easy to generate in electronics, these pulses are ill-adapted to the sharp cutoffs in the US Federal Communications Commission (FCC) mask. The combination of these pulses with passband UWB antennas with steep roll-off improves power efficiency vis-a-vis the FCC mask. This approach is still quite sub-optimal and pulse shaping can provide marked improvement (to 3 dB) over the best traditional combinations. We show that optimal design of UWB waveforms, when taking into account antenna gain profiles, improves the power efficiency of the pulses. Three typical antennas are considered. A nonlinear optimization process is used to design an efficient pulse for each antenna. The proposed optimization is based on the hybrid genetic algorithm and a sequential quadratic program. We demonstrate that this method finds efficient pulses under severe antenna distortion. Simulation results confirm that the optimally designed pulses have superior performance compared to the more common Gaussian monocycle and the Gaussian fifth-derivative pulse.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".