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Record W2576389945 · doi:10.1002/ett.3073

Emerging network architecture and functional design considerations for 5G radio access

2016· article· en· W2576389945 on OpenAlexaboutno aff
Patrick Marsch, Icaro Da Silva, Ömer Bulakçı, Milos Tesanovic, Salah Eddine El Ayoubi, Mikko Säily

Bibliographic record

VenueTransactions on Emerging Telecommunications Technologies · 2016
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsnot available
FundersMinistry of Economy, Trade and Industry
KeywordsMetisArchitectureKey (lock)TelecommunicationsAir interfaceRadio access networkComputer scienceInterface (matter)Systems engineeringEngineeringWirelessComputer securityWorld Wide WebBase stationGeographyMobile station

Abstract

fetched live from OpenAlex

Abstract While there is already a common understanding of the services, which 5th generation (5G) mobile communications systems should support, and the key technology components needed to achieve this, there is still the need for further clarification and consensus among key players on the overall 5G radio access network (RAN) architecture and its detailed functional design. The 5G public private partnership (5G PPP) project METIS‐II has the objective to foster exactly this consensus building before and in the early days of the standardisation work for 5G. This paper lists the 5G RAN design requirements as identified in the project and summarises the latest considerations of METIS‐II on the air interface landscape in 5G, the envisioned logical RAN architecture and related aspects, as well as key functional design considerations in 5G, which have found wide endorsement within the project. Copyright © 2016 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 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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.304
Teacher spread0.228 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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