Impact of Pulse Shapes on the Performance of an Ultra-Wideband Multiple-Access Fast Acquisition System
Bibliographic record
Abstract
Ultra-wideband (UWB) communication systems provide very high data rates by transmitting extremely short duration pulses. The impulse waveform is one of the key factors that influence the performance of these systems. While fulfilling the FCC spectral emission requirements, the pulse shape must offer high detection capabilities with suitable levels of accuracy. In this paper, we evaluate the effect of pulse shapes on the performance of an UWB computationally-efficient acquisition scheme in the presence of multiple user interference (MUI) and Gaussian noise. In the comparisons, different pulses with same duration were used in extensive Monte-Carlo simulations. Results show that the pulse shape has a noticeable impact on the performance of our UWB computationally-efficient acquisition scheme. Moreover, it is concluded that the 6th or the 8th order Gaussian derivative is the most suitable pulse shape to choose, depending on spectral bandwidth requirements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".