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Record W1513136219 · doi:10.1109/vetecf.2004.1400349

Precise bit error rate analysis of bandlimited BPSK with EGC and SC diversity in CCI and Nakagami fading

2005· article· en· W1513136219 on OpenAlexaff
Kathiravetpillai Sivanesan, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFadingNakagami distributionPhase-shift keyingBit error rateBandlimitingFading distributionDiversity gainDiversity combiningAlgorithmMaximal-ratio combiningMathematicsComputer scienceElectronic engineeringStatisticsRayleigh fadingFourier transformEngineering

Abstract

fetched live from OpenAlex

Equal gain and maximum desired user power selection combining for bandlimited BPSK systems in Nakagami fading with cochannel interference are considered. Spectrum raised-cosine and new Beaulieu-Tan-Damen pulse shapes are employed. Average bit error rates are derived using characteristic function and Fourier series methods for arbitrary orders of diversity and fading parameters. The computational complexity of the solution does not grow with the diversity order. Slow flat fading, asynchronous timing and independent fading gains are assumed. The superiority of the Beaulieu-Tan-Damen pulse over the conventional spectrum raised-cosine pulse in bit error rate performance is observed and the superiority increases with the diversity order.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.041
GPT teacher head0.284
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 designObservational
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

Citations2
Published2005
Admission routes1
Has abstractyes

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