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Record W2532241206 · doi:10.1109/epc.2008.4763305

Characterization of fixed wireless channels between 200 MHz and 2 GHz for intelligent grid applications in suburban macrocell environments

2008· article· en· W2532241206 on OpenAlexaff
Anthony Liou, Kyle N. Sivertsen, Pouyan Arjmandi, Ganapathy Viswanathan, Boubacar Diallo, Sol Lancashire, David G. Michelson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsBC Hydro (Canada)University of British Columbia
Fundersnot available
KeywordsFadingMacrocellPath lossWirelessRadio spectrumComputer scienceElectronic engineeringGridNon-line-of-sight propagationShadow mappingFading distributionTelecommunicationsChannel (broadcasting)EngineeringGeographyRayleigh fadingBase station

Abstract

fetched live from OpenAlex

Growing interest in the wireless-enabled intelligent grid has prompted spectrum regulators to re-allocate various bands between 200 MHz and 2 GHz to fixed wireless applications. Although it is well-known that fixed wireless channels are subject to fading due to the motion of scatterers in the environment, most past efforts to characterize such fading on non-line-of-sight links in suburban macrocell environments have focused on frequency bands at 2 GHz and above. Based upon received signal strength data that we collected simultaneously in the 220, 850 and 1900 MHz bands at ranges between 1 and 4 km from a set of transmitting antennas located at 80 m above ground level, we have investigated the manner in which path loss and signal fading vary with distance at lower frequencies in such environments. Our results show that the severity of fading increases rapidly as both the carrier frequency and path loss increase.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.362

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 communication0.0000.000
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 head0.021
GPT teacher head0.223
Teacher spread0.202 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2008
Admission routes1
Has abstractyes

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