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Record W2940916153 · doi:10.1049/iet-com.2018.6075

NOMA‐based cooperative relaying for secondary transmission in cognitive radio networks

2019· article· en· W2940916153 on OpenAlex
Yuzhi Chu, Benoı̂t Champagne, Wei‐Ping Zhu

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

VenueIET Communications · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsConcordia UniversityMcGill University
FundersNanjing University of Posts and TelecommunicationsNational Natural Science Foundation of China
KeywordsCognitive radioNomaComputer scienceTransmission (telecommunications)Computer networkTelecommunicationsWirelessTelecommunications link

Abstract

fetched live from OpenAlex

In this study, the authors present and investigate a novel cooperative relaying scheme for cognitive radio networks (CRNs), which is based on non‐orthogonal multiple access (NOMA). In the proposed scheme, following the detection of an idle channel, the secondary base station transmits a power domain NOMA signal to a first nearby secondary user (SU). In addition to decoding its own signal, this user applies a decode‐and‐forward strategy to relay the signal intended to a second SU. In contrast to previous works, where the spectrum sensing and transmission phases are treated separately, the authors here consider both phases jointly in the design and analysis of the proposed scheme. To characterise performance of the latter, analytical expressions are derived for the outage probability and the ergodic rate of the two SUs by assuming a flat Rayleigh fading channel model. The performance of two traditional orthogonal multiple access schemes is also analysed for comparison. Simulation and numerical results are presented to demonstrate the effectiveness of the proposed cooperative relaying scheme for CRN, as well as the accuracy of the analytical results.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.282
Teacher spread0.256 · 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