Optimal Error Rate Performance of Binary TH-UWB Receivers in Multiuser Interference
Bibliographic record
Abstract
An exact mathematical model which explains the important characteristics of the probability density function (PDF) of the multiple access interference (MAI) in time-hopping UWB (TH-UWB) systems is discussed. The proposed model accurately foresees impulses, singularities, and heavy tails found in the distribution of the MAI. Also, it discloses precisely why a Gaussian approximation for the MAI in TH-UWB systems is highly inaccurate even in the presence of a large number of interferers. Then, using the maximum a posteriori (MAP) receiver rule and based on the obtained model for the PDF of the MAI, the optimal achievable BER performance of binary TH-UWB receivers is numerically determined. Finally, the performances of some recently proposed UWB receivers are benchmarked against the optimal performance.
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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".