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Record W2613683030 · doi:10.1109/wcnc.2017.7925970

Multi-Antenna Down-Link Cooperative Systems over Composite Multipath/Shadowing Channels

2017· article· en· W2613683030 on OpenAlexafffund
Eylem Erdoğan, Ali Afana, Salama Ikki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaTürkiye Bilimsel ve Teknolojik Araştırma KurumuLakehead University
KeywordsFadingMultipath propagationShadow mappingComputer scienceHop (telecommunications)Topology (electrical circuits)Path lossMIMOChannel (broadcasting)Antenna (radio)Link levelAlgorithmElectronic engineeringComputer networkMathematicsTelecommunicationsWirelessEngineering

Abstract

fetched live from OpenAlex

In this paper, we investigate the effects of shadowing and multi-path fading on a MIMO down-link amplify-and-forward (AF) dual-hop network. In the system, antenna selection is adopted at the first hop based on the shadowing information and we assume both hops undergo Generalized-K composite fading channel. For the considered model, approximate lower bound outage and error probability expressions are derived and asymptotic analysis is performed to investigate the effects of shadowing on the system performance. Moreover, the power allocation optimization problem is studied where optimal power values are obtained. Finally, the analytical findings are validated by the 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0030.002
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 head0.076
GPT teacher head0.320
Teacher spread0.244 · 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
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

Citations7
Published2017
Admission routes2
Has abstractyes

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