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Record W2134285433 · doi:10.1109/icc.2008.807

Amplify-and-Forward Cooperative Systems with Fixed Gain Relays

2008· article· en· W2134285433 on OpenAlexaff
Golnaz Farhadi, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFadingDiversity gainHop (telecommunications)Computer scienceProbability density functionChannel (broadcasting)Transmission (telecommunications)Topology (electrical circuits)WirelessCooperative diversityCommunications systemProbability of errorBit error rateAlgorithmMathematicsTelecommunicationsStatistics

Abstract

fetched live from OpenAlex

Multi-hop and multi-branch wireless transmission systems with nonregenerative fixed gain relays employing amplify-and-forward relaying are studied. Simple closed-form expressions for the outage and bit error probabilities of these systems are derived. The analysis is valid for an arbitrary number of hops, arbitrary number of branches and any fading channel model whose signal power probability density function has nonzero value at the origin. It is shown that while a multi-hop transmission system does not offer diversity gain, it can perform better than a single hop system if its average individual link SNRs satisfy a certain condition. In addition, the analysis clearly shows the diversity gains achieved by multi-branch systems for any fading channel model.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.358

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 science0.0000.000
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 head0.041
GPT teacher head0.250
Teacher spread0.208 · 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 designTheoretical or conceptual
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
Published2008
Admission routes1
Has abstractyes

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