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Record W2115254362 · doi:10.1109/vetecs.2005.1543538

Analysis of Average Signal-to-Interference-Noise Ratio for Indoor UWB Rake Receiving System

2005· article· en· W2115254362 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsSimon Fraser University
FundersMedical Research CouncilInha University
KeywordsRakeInterference (communication)Computer scienceAsynchronous communicationRake receiverSignal-to-interference-plus-noise ratioElectronic engineeringNoise (video)Channel (broadcasting)Signal-to-noise ratio (imaging)Transmission (telecommunications)WirelessUltra-widebandTelecommunicationsComputer networkFadingEngineeringPhysicsPower (physics)

Abstract

fetched live from OpenAlex

In this paper, we derive an analytical expression for average signal-to-interference-plus-noise ratio (SINR) for ultra wideband (UWB) Rake receiver in an indoor multiuser communication scenario, given that the interference level is fluctuating due to asynchronous transmission among different users. The indoor wireless channel model adopted here is a standard channel model recently released by IEEE 802.15 study group 3a. We propose a theoretical framework to analyze the average SINR and show that our analysis is well coincident with the simulation results. Finally, we show that our result can be used to theoretically determine the optimum integration interval for a single-user UWB transmitted reference (TR) system.

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 score0.748
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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

Quick stats

Citations17
Published2005
Admission routes1
Has abstractyes

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