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Record W4313365403 · doi:10.1109/nana56854.2022.00007

Keynotes

2022· article· en· W4313365403 on OpenAlexaff
Han Pin-, Han Ho, Zhou Su

Bibliographic record

Venue2022 International Conference on Networking and Network Applications (NaNA) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceProvisioningArchitectureComputer networkLeverage (statistics)Base stationTelecommunicationsKey (lock)Computer security

Abstract

fetched live from OpenAlex

Indoor services contribute over 70% of the traffic in the current mobile system, and are expected to more dominate in the 5G era. Thus, an indoor system that can ensure line-of-sight (LOS) transmission with the end users in each indoor chamber will play a key role in achieving efficient operation of the 5G mobile systems. The talk firstly gives an overview on the indoor systems that have been reported and commercially deployed. Then a new antenna access architecture for the indoor service provisioning will be introduced. Specifically, the architecture leverage an all-analog link to communicate between the antenna unit and the Base station via a LAN cable (i.e., Cat5,6,7). We will highlight the issues of the architecture and its implementation in the real world.

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 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 score0.991
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.244
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 teacher head, 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

Citations0
Published2022
Admission routes1
Has abstractyes

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