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Record W2982493600 · doi:10.1109/wcnc.2019.8886042

Secrecy Analysis of a TAS/MRC Scheme in $\alpha-\mu$ Fading Channels

2019· article· en· W2982493600 on OpenAlexaff
Jules M. Moualeu, Daniel Benevides da Costa, F. Javier López‐Martínez, Walaa Hamouda, Telex M. N. Ngatched, Ugo Silva Dias

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsMemorial University of NewfoundlandConcordia University
Fundersnot available
KeywordsSecrecyFadingMaximal-ratio combiningMIMOAntenna (radio)Computer scienceOutage probabilityMonte Carlo methodElectronic engineeringComputer networkDiversity gainTopology (electrical circuits)TelecommunicationsStatisticsMathematicsChannel (broadcasting)EngineeringComputer securityElectrical engineering

Abstract

fetched live from OpenAlex

This paper investigates the secrecy performance of a multiple-input multiple-output (MIMO) system with transmit antenna selection (TAS) and maximal-ratio combining (MRC) over generalized α-μ fading. In the underlying wireless communication system, a single antenna is selected to transmit confidential messages to a multi-antenna receiver in the presence of a passive multi-antenna eavesdropper. In our analysis, new closed-form expressions are obtained for the secrecy outage probability (SOP) and the probability of strictly positive secrecy capacity (SPSC), and are subsequently corroborated through Monte Carlo simulations to assess their validity. Moreover, asymptotic studies of the secrecy outage probability are derived and explicitly show the effects of various system parameters on the secrecy diversity gain.

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 score0.717
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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