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Record W2067706152 · doi:10.1109/tvt.2014.2378813

Jamming in Dual-Hop Amplify-and-Forward Relaying

2014· article· en· W2067706152 on OpenAlexaff
Aydin Behnad, Xianbin Wang

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2014
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsWestern University
Fundersnot available
KeywordsJammingNakagami distributionRelayRayleigh fadingFadingHop (telecommunications)Computer sciencePower (physics)Interference (communication)Outage probabilityTransmitter power outputElectronic engineeringTransmission (telecommunications)Computer networkTelecommunicationsEngineeringTransmitterPhysicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

The performance of a dual-hop amplify-and-forward (AF) relaying system in the presence of a jammer is analyzed by obtaining the end-to-end outage probability for the scenario where the system is interference limited and operates in either Nakagami-0.5 or Rayleigh fading environments. Then, the optimal power allocation and transmission toward the relay and the destination for maximizing the outage probability is analyzed. It is shown that for both fading environments when the jammer power is sufficiently large, jamming the relay and the destination with equal power allocation is optimal, whereas when the jamming power is low, more power should be allocated to jam any of the source-relay and relay-destination links having lower receiving signal power. In addition, the difference between the optimal and the equal power allocation performance is investigated. Analytical results are verified and illustrated by some numerical results and simulations.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.579

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 integrity0.0000.001
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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 designOther design
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

Citations5
Published2014
Admission routes1
Has abstractyes

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