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Record W2021606815 · doi:10.1109/icuwb.2014.6958951

60 GHz wireless data center channel measurements: Initial results

2014· article· en· W2021606815 on OpenAlexaff
Mohammed Zakarya Zaaimia, R. Touhami, Vincent Fono, Larbi Talbi, Mourad Nedil

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec en Outaouais
Fundersnot available
KeywordsAisleChannel (broadcasting)Radio channelComputer scienceDelay spreadPath lossReal-time computingWirelessData setAlgorithmRay tracing (physics)Computer networkEngineeringMultipath propagationTelecommunicationsPhysicsOptics

Abstract

fetched live from OpenAlex

This paper reports initial results of wireless data center (WDC) 60 GHz radio channel measurements in a real data center. A channel sounder based on a vector network analyzer is used to measure the channel transfer function. In addition, ray-tracing simulations are conducted to verify the measurements accuracy. Data post processing procedure is presented to derive the power delay profiles (PDP). PDPs are processed using a peak detection algorithm for quick clusters enumeration. Two measurement sets are considered, namely neighbor racks scenario set and cross aisle scenario set. It is found that ray-tracing simulations results show a reasonable agreement for both sets. Cluster number and path loss results exhibit a slight difference for the two sets. Moreover, path loss results of neighbor racks scenarios show a 3 dB better link budget compared to cross aisle scenarios.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.135
GPT teacher head0.283
Teacher spread0.148 · 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 designObservational
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

Citations13
Published2014
Admission routes1
Has abstractyes

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