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Using the Wireless and PLC Channels for Diversity

2012· article· en· W1997394709 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 Communications · 2012
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSubcarrierWirelessDiversity combiningComputer scienceSignal-to-noise ratio (imaging)Maximal-ratio combiningElectronic engineeringNarrowbandOrthogonal frequency-division multiplexingThroughputDiversity schemeBit error rateComputer networkFadingChannel (broadcasting)EngineeringTelecommunications

Abstract

fetched live from OpenAlex

Performance of indoor home networks can be improved by simultaneous use of wireless and powerline communication (PLC) channels. A narrowband model representing an OFDM subcarrier is used to analyze the performance of several diversity combining schemes including optimum combining (OC), saturated metric combining (SMC) and maximal ratio combining (MRC). Results from BER analysis show that SMC achieves good performance in highly impulsive noise and is relatively insensitive to error in noise parameter estimates. Indoor measurements from 3 detached homes show that parallel wireless and PLC channels have a wide, but similar, signal-to-noise ratio (SNR) range. Measurement data is used with link throughput analysis to show that wireless/PLC diversity can be used to minimize the likelihood of low throughput links.

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 categoriesScience and technology studies
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 score0.932
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.105
GPT teacher head0.301
Teacher spread0.195 · 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