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Record W2333118136 · doi:10.1109/lcomm.2016.2549011

Secure Communications in Underlay Cognitive Radio Networks: User Scheduling and Performance Analysis

2016· article· en· W2333118136 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Communications Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEavesdroppingComputer scienceComputer networkUnderlayScheduling (production processes)Cognitive radioTelecommunications linkSecrecyTransmitterCognitive networkTelecommunicationsSignal-to-noise ratio (imaging)WirelessComputer securityEngineering

Abstract

fetched live from OpenAlex

This letter investigates secure communications against eavesdropping in an underlay cognitive radio network. The secondary users do not know the interference level that they receive from the primary transmitter, and thus, secondary transmissions may experience outages. We consider an outage probability threshold for secondary transmissions, and propose secondary user scheduling schemes for downlink and uplink, targeting at maximizing the achievable secrecy rate. We derive closed-form secrecy outage probability and show that the proposed user scheduling schemes can achieve full secrecy diversity.

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 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 score0.741
Threshold uncertainty score0.905

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.025
GPT teacher head0.268
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