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Record W1966272865 · doi:10.1002/wcm.783

A bandwidth-efficient cooperative relaying scheme with hard interference cancellation and iterative decoding

2008· article· en· W1966272865 on OpenAlexaff
Ho Van Khuong, Tho Le‐Ngoc

Bibliographic record

VenueWireless Communications and Mobile Computing · 2008
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsMcGill University
Fundersnot available
KeywordsRelayComputer scienceSingle antenna interference cancellationDecoding methodsBandwidth (computing)Relay channelTransmission (telecommunications)Spectral efficiencyDiversity gainElectronic engineeringAntenna diversityInterference (communication)Computer networkTelecommunicationsWirelessFadingPower (physics)BeamformingEngineeringChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

Abstract This paper considers a coded cooperative relaying scheme in which all successfully decoded signals from multiple sources are simultaneously forwarded by a multi‐antenna relay to a common multi‐antenna destination to increase bandwidth efficiency. Iterative decoding with hard interference cancellation is used at destination to recover user information. By using orthogonal transmission from sources to avoid their mutual interference, the multi‐antenna relay offers receive space diversity that greatly enhances the decoding performance at the relay. This makes the source‐relay transmission more robust, less sensitive to the source‐relay link SNR, and hence increases the contribution of the relay in cooperative transmission. Simulation results show that the proposed scheme significantly outperforms direct transmission under the same transmit power and bandwidth efficiency. Copyright © 2009 John Wiley & Sons, Ltd.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.043
GPT teacher head0.277
Teacher spread0.234 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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