MétaCan
Menu
Back to cohort
Record W2136640249 · doi:10.1109/wcnc.2006.1683568

Multi-user interference performance comparison of direct-sequence impulse radio and direct-sequence UWB in AWGN

2006· article· en· W2136640249 on OpenAlexaff
Bo Hu, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAdditive white Gaussian noiseComputer scienceBit error rateDirect-sequence spread spectrumTime-hoppingSpread spectrumKeyingPhase-shift keyingElectronic engineeringAlgorithmTelecommunicationsDecoding methodsWhite noiseEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

A new ultra-wide bandwidth communication system using both a time-hopping sequence and a direct spreading sequence, called direct-sequence impulse radio, has recently been proposed. The performance of this new scheme in multi-user interference is investigated. A precise expression for calculating the bit error probability of direct-sequence impulse radio is derived. Our precise analysis indicates that the Gaussian approximation substantially overestimates the performance at large values of signal-to-noise power ratio. Ultra-wideband communication systems employing time-hopping, direct-sequence and the newly proposed direct-sequence impulse radio schemes operating in multi-user interference are accurately compared in terms of the bit error rate. Our results indicate that direct-sequence impulse radio outperforms the time-hopping binary phase-shift keying system. However, its performance is poorer than the performance of conventional direct sequence binary phase-shift keying systems

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.265
Teacher spread0.240 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicUltra-Wideband Communications TechnologyFrench-language works237,207