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Record W4366758407 · doi:10.7753/ijcatr0507.1013

5G Wireless Technology- An overview of the current Trends

2023· article· en· W4366758407 on OpenAlexaboutno aff
Muhammad Irfan, Jan Sher, Naveed Ullah, Muhammad Sulaiman, Junaid Saleem

Bibliographic record

VenueInternational Journal of Computer Applications Technology and Research · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceCurrent (fluid)WirelessTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

Wireless technology networks or 5th Generation wireless systems which is used for videos and audios communication announcement the next major time period of mobile telecommunications Criterions time the current next Generation mobile networks confederated .inthis paper we are studying different Technologies in 5G The handover of 5G the Models of 5G its architecture, its different components and METIS Task Force Networks.2-Day video recording is available.Its components access/backhaul integration, direct device-to-device communication, flexible duplex, flexible spectrum usage multiantenna transmission, ultra-lean design, user/control separation architecture of 5G is highly advanced, its network elements and various terminals are characteristically upgraded to afford a new situation.Likewise, service providers can implement the advance technology to adopt the value-added services easily.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.402
Teacher spread0.352 · 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 designOther design
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

Citations2
Published2023
Admission routes1
Has abstractyes

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