Modeling of multiple access interference and BER derivation for TH and DS UWB multiple access systems
Bibliographic record
Abstract
A novel analytical method is introduced for exact statistical modeling of multiple access interference (MAI), in time hopping pulse position modulation and pulse amplitude modulation (TH-PPM and TH-PAM) ultra wideband (UWB) systems operating in additive white Gaussian noise (AWGN) channels. Based on this method, exact bit error rates (BER) are expressed in simple formulas. In a similar fashion, the exact BER of direct sequence (DS) UWB is also derived for PAM modulation. The proposed modeling of MAI considers complete asynchronism in user access, and is also suitable for accurately modeling the MAI components contributed by individual paths in channels with Poisson arrivals, based on the time variables. We further extend this method to derive general expressions for the BER performance in log-normal fading multi-path channels. In the course of these derivations, we also introduce a more accurate numerical approach to evaluate the characteristic function (CF) of a lognormal random variable
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".