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Record W2114000865 · doi:10.1109/lcomm.2006.060849

A Noise Reduction Amplify-and-Forward Relay Protocol for Distributed Spatial Diversity

2006· article· en· W2114000865 on OpenAlexaff
Norman C. Beaulieu, Jeremiah Hu

Bibliographic record

VenueIEEE Communications Letters · 2006
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRelayTransmission (telecommunications)Computer scienceNoise (video)Antenna diversityWirelessProtocol (science)Computer networkSignal-to-noise ratio (imaging)Relay channelTelecommunicationsElectronic engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Amplify-and-forward transmission has been shown to be a viable transmission protocol for wireless networks incorporating distributed spatial diversity. A drawback of this relatively simple transmission protocol is identified. In addition to signal amplification, perpendicular noise at the relay is also amplified. A method to reduce the noise at the relay prior to amplification is proposed. To demonstrate the improvement of this protocol, we consider single-user single-relay transmission and show that by eliminating perpendicular noise at the relay, the outage region boundaries are reduced. Perpendicular noise elimination is inherent in decode-and-forward relaying. Hence, Fair comparisons of amplify-and-forward relaying with decode-and-forward relaying are based on noise reduced amplify-and-forward relaying

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
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 head0.055
GPT teacher head0.307
Teacher spread0.252 · 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 designNot applicable
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

Citations11
Published2006
Admission routes1
Has abstractyes

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