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Record W2300078924 · doi:10.1049/iet-com.2015.0278

Impact of spatial correlation on the BER performance of cooperative wireless relay networks with OSTBC

2016· article· en· W2300078924 on OpenAlexaff
Mohammad Torabi, Jean‐François Frigon, David Haccoun

Bibliographic record

VenueIET Communications · 2016
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRelayComputer scienceWirelessCorrelationWireless networkSpatial correlationComputer networkTelecommunicationsMathematicsPhysics

Abstract

fetched live from OpenAlex

In this study, the authors analyse the impact of spatial correlation on the average bit error‐rate (BER) performance of amplify‐and‐forward cooperative relay networks employing Alamouti orthogonal space‐time block coding (OSTBC) over Rayleigh fading channels. Closed‐form expressions are derived for the moment generating function of the total signal‐to‐noise‐ratio (SNR). The authors then obtain closed‐form expressions for the average BER of the system as well as asymptotic expressions for the average BER at high SNRs. To quantify the effects of antenna correlation on the system performance, numerical results are provided and compared for different cases.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.033
GPT teacher head0.282
Teacher spread0.248 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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