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Record W2108113527 · doi:10.1109/icassp.2006.1660974

Error Rate Analysis of Phase-Modulated OFDM (OFDM-PM) in Awgn Channels

2006· article· en· W2108113527 on OpenAlexaff
R.A. Pacheco, Dimitrios Hatzinakos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingAdditive white Gaussian noiseQuadrature amplitude modulationSpectral efficiencyModulation (music)Phase noiseTransmission (telecommunications)Bit error rateElectronic engineeringQAMComputer scienceTelecommunicationsPhysicsWhite noiseEngineeringDecoding methodsChannel (broadcasting)Acoustics

Abstract

fetched live from OpenAlex

QAM transmission of OFDM signals achieves good spectral efficiency while greatly simplifying the equalization process. However, RF transmitters must be operated in their linear region and highly stable oscillators (low phase-noise) are a necessity or the BER will degrade significantly. If angle-modulation is instead used, then the RF signal has constant envelope and phase-noise has an additive effect, the result being more efficient power transmission and orthogonality is maintained with a noisy oscillator. Angle-modulation has lower spectral efficiency then QAM and angle-demodulators suffer a threshold effect: the receiver output SNR degrades, significantly once below a certain input SNR. To apply angle-modulated OFDM systems in practice this threshold effect and ifs impact on the BER (for a given spectral efficiency) must be analyzed. This paper is the first to present such an analysis for phase-modulation (OFDM-PM) in AWGN channels

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: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

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