Optimal Pulse Shaping for Pulse Position Modulation UWB Systems with Sparsity-Driven Signal Detection
Bibliographic record
Abstract
In this paper, we study the problem of optimal pulse shaping for pulse position modulation (PPM) ultra-wideband (UWB) systems with a recently proposed sparsity-driven signal detection method. This signal detection method offers superior performance over traditional matched filter based detection through the representation of additive white Gaussian noise (AWGN) and the UWB pulses via atoms from a Hadamard Walsh matrix and a pulse constellation dictionary, respectively. Recognizing the possibility to further improve the performance with sparsity-driven signal detection through shaping the UWB pulses to be dissimilar to AWGN, we formulate an optimal pulse shaping problem considering the federal communication commission (FCC) emission mask. We also develop a relaxation method to approximate the objective function, and solve the relaxed problem with classical nonlinear programming. Design examples are given to show the resulting pulse shape, its dissimilarity to the channel noise, and its compliance with the mandatory FCC emission mask.
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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 | 0.000 | 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".