A Method for Spectrum Shaping and NBI Suppression in UWB Communications
Bibliographic record
Abstract
This paper investigates spectrum shaping in ultrawideband (UWB) communications in order to introduce spectral nulls to limit interference with narrowband signals. Each transmitted symbol is represented by a monocycle "coded" Gaussian pulse, where use of the monocycle Gaussian pulse ensures that the UWB spectrum mask established by the Federal Communications Commission (FCC) is met and where the codeword is designed to generate a spectral null at the frequency or frequencies being used by existing narrowband devices. Signals obtained with different spectrum shapings (e.g., Butterworth, Chebyshev, elliptical) and by introducing nulls at multiple interference frequency bands are discussed. The performance of a monocycle coded UWB system with a spectral null in the presence of narroband interference (NBI) using single carrier block transmission with frequency domain equalization (SC-FDE) is simulated and compared with that of an uncoded SC-FDE UWB system using a single Gaussian monocycle. Our results show that NBI can be effectively suppressed by transmitting and matched filtering the pulse with a spectral null at the interference frequency, therefore improving the robustness of SC-FDE UWB to NBI.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".