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Record W3216897496 · doi:10.32920/ryerson.14662389.v1

Wavelet OFDM for Power Line Communication

2021· preprint· en· W3216897496 on OpenAlexafffund
Sagar Chandra Kar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsToronto Metropolitan University
FundersMitacs
KeywordsCyclic prefixPower-line communicationOrthogonal frequency-division multiplexingComputer scienceElectronic engineeringFast Fourier transformWavelet transformWaveletBandwidth (computing)Spectral efficiencyTransmission (telecommunications)Channel (broadcasting)Real-time computingPower (physics)TelecommunicationsAlgorithmEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Power Line Communication (PLC) system offers cheaper mode of signal communication facilities. In fast Fourier transform (FFT) based multicarrier PLC system, a cyclic prefix (CP) of the same length of the channel impulse response is added to each symbol in order to transmit data. As a result, there is always an inherent wastage of bandwidth and resources. This research presents a wavelet transform based orthogonal frequency division multiplexing (WTOFDM) approach that eliminates the need for these cyclic prefix and improves the efficiency of the PLC transmission. The presented PLC model is designed for faster and efficient transmission over the power line. The obtained results indicate that the proposed approach enhances the transmission throughput; provides better performance for impulsive noise, and increases the efficiency of the PLC system as a whole. In the end a performance comparison of different wavelet techniques have also been incorporated.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.772
Threshold uncertainty score0.845

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 science0.0010.001
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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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 designNot applicable
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
Published2021
Admission routes2
Has abstractyes

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