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Record W2086270857 · doi:10.1109/icc.2006.255558

Performance Analysis of Space-Time Diversity in Multiuser CDMA Systems over Fading Channels

2006· article· en· W2086270857 on OpenAlexaff
Mohamed AlJerjawi, Walaa Hamouda

Bibliographic record

Venue2006 IEEE International Conference on Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsRayleigh fadingFadingComputer scienceProbability density functionDiversity schemeMultiuser detectionCode division multiple accessAlgorithmAntenna diversityTime diversitySpread spectrumBlock codeMathematicsTelecommunicationsStatisticsDecoding methodsWireless

Abstract

fetched live from OpenAlex

In this work we examine the probability of error performance for a multiuser DS-CDMA system that exploits spatial and temporal diversities over fast-fading Rayleigh channels using a space-time block coding scheme. We commence the analysis by finding the probability density function (pdf) for the signal to interference ratio (SIR). Then, using this pdf, a closed form expression for the probability of error using the decorrelator multiuser detector is obtained. We verify the accuracy of this expression by comparison with simulations for different number of users. Both theoretical and simulation results show that the diversity order is maintained irrespective of the system load.

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)0.003
metaresearch head score (Gemma)0.013
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.304
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 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

Citations4
Published2006
Admission routes1
Has abstractyes

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