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Record W6901551495 · doi:10.60692/gs0c0-8ch92

The Leaky Feeder, a Reliable Medium for Vehicle to Infrastructure Communications

2022· article· en· W6901551495 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2022
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTransmitterQuadrature (astronomy)TransceiverTransmission (telecommunications)Antenna (radio)Bit error rateBroadbandRayleigh fadingWireless

Abstract

fetched live from OpenAlex

Reliable vehicular communications is fast becoming a necessity. Vehicle to infrastructure (V2I) communication, which is critical for safety, is often interrupted when vehicles travel in tunnels. Leaky Feeder (LF) or radiating cable have been the primary solution to provide wireless access in tunnels and mines, but being overlooked until now. The LF is a natural multi antenna transceiver ideal for broadband short rage access. In this work, we model the LF as a linear antenna array and derive the average bit error rate (BER) in Rayleigh fading channel considering Quadrature Phase Shift Keying (QPSK) and M-Array Quadrature Amplitude (M-QAM) Modulations. We consider maximal ratio transmission (MRT) at the transmission end and coherent detection and maximal ratio combining (MRC) at the receiving end. Analytical expressions are derived for the BER. The effects of slot spacing and carrier frequency on the BER are also studied. Numerical evaluations show that the LF is a strong candidate for tunnels with much lower BER than a single antenna transmitter with the same SNR.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.642

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 science0.0000.000
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 head0.031
GPT teacher head0.211
Teacher spread0.180 · 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 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
Published2022
Admission routes1
Has abstractyes

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