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Record W3127861993 · doi:10.1109/lcomm.2021.3057850

Secrecy Outage Probability and Average Rate of RIS-Aided Communications Using Quantized Phases

2021· article· en· W3127861993 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Communications Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsConcordia UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsSecrecyOutage probabilityComputer scienceArtificial noiseSignal-to-noise ratio (imaging)Scaling lawPhase (matter)TelecommunicationsStatistical physicsApplied mathematicsTopology (electrical circuits)ScalingTheoretical computer scienceMathematicsPhysical layerWirelessFadingPhysicsComputer securityCombinatorics

Abstract

fetched live from OpenAlex

This letter provides a unified performance analysis of secure reconfigurable intelligent surface (RIS)-assisted communications in the presence of discrete phase shifts. In particular, we derive exact secrecy outage probability in the presence of non-colluding and colluding eavesdroppers, and we obtain the corresponding diversity orders. Moreover, analytical expressions of the average secrecy rate and different scaling laws with sufficiently large signal-to-noise ratio and number of RIS reconfigurable elements are derived. Simulation results corroborate our theoretical 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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.081
GPT teacher head0.306
Teacher spread0.225 · 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