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Record W2171744213 · doi:10.1109/twc.2006.04530

Modeling of multiple access interference and BER derivation for TH and DS UWB multiple access systems

2006· article· en· W2171744213 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAdditive white Gaussian noiseBit error rateFadingAlgorithmUltra-widebandPulse-position modulationComputer scienceTime-hoppingModulation (music)Nakagami distributionInterference (communication)MathematicsChannel (broadcasting)Pulse-amplitude modulationTelecommunicationsDecoding methodsPulse (music)Physics

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.687
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.276
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it