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Record W2143021806 · doi:10.1109/glocom.2005.1577887

Precise bit error probability analysis of DCT OFDM in the presence of carrier frequency offset on AWGN channels

2005· article· en· W2143021806 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

VenueGLOBECOM '05. IEEE Global Telecommunications Conference, 2005. · 2005
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingAdditive white Gaussian noisePhase-shift keyingDiscrete cosine transformCarrier frequency offsetQuadrature amplitude modulationComputer scienceBit error rateAlgorithmElectronic engineeringFrequency offsetQAMDiscrete Fourier transform (general)KeyingMathematicsTelecommunicationsWhite noiseFourier transformFractional Fourier transformDecoding methodsEngineeringChannel (broadcasting)Fourier analysis

Abstract

fetched live from OpenAlex

A precise method for calculating the bit error probability of a discrete cosine transform (DCT)-based orthogonal frequency-division multiplexing (OFDM) system on AWGN channels in the presence of frequency offset is derived. These accurate results are used to examine and compare the bit error probability performances of a DCT-OFDM system and the conventional discrete Fourier transform (DFT)-based OFDM system. Several signaling formats, such as binary phase shift keying (BPSK), quaternary phase shift keying (QPSK), and 16-ary quadrature amplitude modulation (16-QAM) are considered. Analysis and simulation results show that the DCT-OFDM system outperforms the DFT-OFDM system in the presence of carrier frequency offset.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.296
Teacher spread0.254 · 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