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Record W2118327116 · doi:10.1049/iet-com.2013.0646

Improving spectrum access using a beam‐forming relay scheme for cognitive radio transmissions

2014· article· en· W2118327116 on OpenAlexaff
Wael Jaafar, Wessam Ajib, David Haccoun

Bibliographic record

VenueIET Communications · 2014
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversité du Québec à MontréalPolytechnique Montréal
Fundersnot available
KeywordsCognitive radioComputer scienceRelayScheme (mathematics)Computer networkTelecommunicationsSpectrum (functional analysis)WirelessPhysicsMathematics

Abstract

fetched live from OpenAlex

Cognitive radio (CR) systems allow unlicensed secondary users to transmit on the licensed frequency bands without degrading the transmissions of licensed primary users. Combining CR with other emerging techniques such as multi‐antenna relaying may bring many benefits for the secondary transmissions. In this study, the authors propose and investigate a new relay‐based cooperation scheme for a CR network to improve the secondary access to the licensed spectrum band without causing additional interference to the simultaneous primary transmission. The proposed scheme considers one multi‐antenna relay node that can assist either the primary or the secondary transmission using beam‐forming (BF). In the proposed new scheme, the BF weights are designed in the presence of imperfect channel state information (CSI). Simulation results show that the secondary's channel capacity is significantly improved and outperforms conventional transmission schemes. The results also reveal the impact of imperfect CSI on the primary outage performance and the efficiency of the proposed solution for minimising the interference due to imperfect CSI.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
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 head0.050
GPT teacher head0.319
Teacher spread0.269 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2014
Admission routes1
Has abstractyes

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