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Record W2130301039 · doi:10.1109/atc.2008.4760613

A multi-agent protocol to manage interference in a distributed base station system

2008· article· en· W2130301039 on OpenAlex
Philippe Leroux, Sébastien Roy, Jean‐Yves Chouinard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsComputer scienceBase stationComputer networkInterference (communication)RelayProtocol (science)Distributed computingWirelessWireless networkChannel (broadcasting)MacroScheme (mathematics)Topology (electrical circuits)EngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a protocol to manage multi-user interference (MUI) in a distributed base station system (DBS). Traditional cellular communication schemes are based on one-to-one wireless links. In a DBS scheme, more than one station can relay the same mobile. Hence, interference patterns cannot be handled by conventional means. The protocol proposed herein answers the problem of assigning channels to mobiles having dynamically changing sets of DBS (because of optimization and mobility) linking each of them to the network with a macro-diversity gain. It is also completely distributed and dynamic. It adapts to virtually any change in topology so that the communication network does not require explicit configuration. It is shown that a feasible operating point can be reached to make use of macro-diversity while maximizing channel reusability and limiting the effect of interference.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.373

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.082
GPT teacher head0.340
Teacher spread0.257 · 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

Quick stats

Citations7
Published2008
Admission routes1
Has abstractyes

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