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Record W2134634099 · doi:10.1109/pimrc.2006.254421

The Performance of Soft Macrodiversity Based on Maximal-Ratio Combining in Uncorrelated Rician Fading

2006· article· en· W2134634099 on OpenAlexaff
Philippe Leroux, Sébastien Roy, Jean‐Yves Chouinard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRician fadingFadingMaximal-ratio combiningBit error rateMathematicsFading distributionUncorrelatedAlgorithmStatisticsQuadrature amplitude modulationTelecommunicationsComputer scienceRayleigh fadingDecoding methods

Abstract

fetched live from OpenAlex

In this paper, a simple product expression is found for the DPSK bit error rate of distributed base station systems affected by Rician fading. In this context, the received signals' fading envelopes are Rician, uncorrelated among themselves, and in general have different variances and K factors. It is assumed that maximal-ratio diversity combining is applied. This bit error rate expression is extended to cover QAM modulation via approximation. Furthermore, a new product form of the probability density function (PDF) for a sum of non-central chi-square variates with different variances is derived, since it constitutes a necessary step in our analysis

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 score0.095
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations10
Published2006
Admission routes1
Has abstractyes

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