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Record W2169995684 · doi:10.1109/mwc.2011.6056694

Green last mile: how fiber-connected massively distributed antenna systems can save energy

2011· article· en· W2169995684 on OpenAlexaff
Alireza Attar, Haoming Li, Victor C. M. Leung

Bibliographic record

VenueIEEE Wireless Communications · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of British Columbia
FundersFrench Muscular Dystrophy Association
KeywordsComputer scienceComputer networkDistributed antenna systemWireless broadbandLast mile (transportation)FemtocellRadio over fiberBase stationEnergy consumptionBroadbandWirelessDistributed computingTelecommunicationsWireless networkMileElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

We introduce a novel last-mile architecture that integrates the advantages of a distributed antenna system with centralized processing capability, connected through an optical fiber medium. The proposed broadband wireless access with fiber-connected massively distributed antenna system (BWA-FMDA) is capable of enhancing spectral efficiency of the network through coordinated multipoint transmissions at the femtocell scale. Furthermore, by shortening the lastmile communication link and lowering the power consumption, BWA-FMDA represents a viable green wireless access solution. Through our detailed and extensive simulation results, we demonstrate the potentially superior performance of BWA-FMDA in comparison with micro base station and femtocell deployments.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.213
Teacher spread0.185 · 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 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

Citations55
Published2011
Admission routes1
Has abstractyes

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