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Record W2166194781 · doi:10.1109/lcomm.2014.2347951

Closed Form SER Expressions for QPSK OFDM Systems With Frequency Offset in Rayleigh Fading Channels

2014· article· en· W2166194781 on OpenAlexafffund
Ahmed M. Hamza, J.W. Mark

Bibliographic record

VenueIEEE Communications Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase-shift keyingOrthogonal frequency-division multiplexingFrequency offsetRayleigh fadingFadingRayleigh scatteringOffset (computer science)Fading distributionClosed-form expressionCarrier frequency offsetMathematicsComputer scienceBit error rateTelecommunicationsAlgorithmElectronic engineeringPhysicsMathematical analysisChannel (broadcasting)EngineeringOptics

Abstract

fetched live from OpenAlex

In this letter, the performance of QPSK OFDM systems with frequency offsets is investigated. Closed form expressions for the symbol error rate (SER) that are valid for any frequency offset in Rayleigh fading channels are derived. To achieve this, a modification to the result of the integral of the product of two Q-functions over the Rayleigh distribution is provided. The modification makes the result of this integral valid in any case whether the arguments of the Q-functions are positive or negative. Simulation results are provided to demonstrate the accuracy of the derived expressions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.024
GPT teacher head0.258
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations12
Published2014
Admission routes2
Has abstractyes

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