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Record W2156092280 · doi:10.1109/twc.2008.070226

Optimal precoder for amplify-and-forward half-duplex relay system

2008· article· en· W2156092280 on OpenAlexaff
Yanwu Ding, Jian‐Kang Zhang, Kon Max Wong

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2008
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRelayQuadrature amplitude modulationQAMRelay channelFarey sequenceCoding gainComputer sciencePhase-shift keyingErgodic theoryControl theory (sociology)Bit error rateTopology (electrical circuits)MathematicsDecoding methodsAlgorithmDiscrete mathematicsPhysicsCombinatoricsMathematical analysis

Abstract

fetched live from OpenAlex

In this paper, an optimal unitary precoder is designed for an amplify-and-forward (AF) half-duplex relay system to obtain the maximum coding gain while the original ergodic channel capacity for the relay system is kept unchanged. A closed-form design is derived for quadrature amplitude modulation (QAM) signals by employing the properties of Farey sequence in number theory. Simulation results indicate that the proposed design greatly improves the bit error rate (BER) performance for the relay system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.292
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations29
Published2008
Admission routes1
Has abstractyes

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