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Record W2163473895 · doi:10.1155/asp.2005.306

Performance and Capacity of PAM and PPM UWB Time-Hopping Multiple Access Communications with Receive Diversity

2005· article· en· W2163473895 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

VenueEURASIP Journal on Advances in Signal Processing · 2005
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPulse-position modulationAdditive white Gaussian noiseComputer scienceTime-hoppingDiversity combiningTelecommunicationsPulse-amplitude modulationDiversity gainProbability of errorTime diversityModulation (music)Electronic engineeringChannel capacityFadingSIGNAL (programming language)Channel (broadcasting)AlgorithmPulse (music)PhysicsEngineeringAcoustics

Abstract

fetched live from OpenAlex

The error probability and capacity of a time-hopping ultra-wideband (UWB) communication system with receive diversity are investigated. We consider pulse amplitude modulation (PAM) and pulse-position modulation (PPM) over additive white Gaussian channels for a single-user system. A multiuser environment with PPM is also investigated. It is shown that the communication distance and error performance are improved by employing receive diversity. The channel capacity of PPM and PAM is determined subject to the power constraints of FCC part 15 rules to illustrate the relationship between reliable communication distance and signal-to-noise ratio. The error probability with PAM and receive diversity is derived for the single-user case. The error probability and performance bounds with PPM are derived for both the single-user and multiuser cases.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.480

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 integrity0.0000.001
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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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