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Record W2112943184 · doi:10.1109/icc.1994.368772

π/4-DQPSK on microcellular radio channels with diversity and interference

2002· article· en· W2112943184 on OpenAlexaff
Adnan Abu‐Dayya, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsPhase-shift keyingBit error rateFadingInterference (communication)Maximal-ratio combiningKeyingComputer scienceElectronic engineeringAlgorithmTelecommunicationsMathematicsEngineeringDecoding methodsChannel (broadcasting)

Abstract

fetched live from OpenAlex

A analyze the average bit error rate (BER) performance of /spl pi//4-shifted differential quadrature phase shift keying (/spl pi//4-DQPSK) in the presence of multiple independent cochannel interferers in frequency-nonselective fading environments. Nyquist shaped pulses are used and postdetection diversity combining is employed at the receiver. The use of both L-branch postdetection equal gain combining (EGC) and L-branch postdetection selection combining (SC) are considered. Two approaches for representing the cochannel interference are investigated. These are a Gaussian interference model and a synchronous interference model. The accuracies of both of these models are assessed by comparing their BER performances with precise BER results. The precise BER results are obtained by using a combination of analysis and simulation.>

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.187
Teacher spread0.165 · 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 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
Published2002
Admission routes1
Has abstractyes

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