MétaCan
Menu
Back to cohort
Record W4392564184 · doi:10.4018/ijbdcn.339889

6G Wireless Communication Networks

2024· article· en· W4392564184 on OpenAlexfundno aff
Md. Alimul Haque, Sultan Ahmad, Ali J. Abboud, Md. Alamgir Hossain, Kailash Kumar, Shameemul Haque, Deepa Sonal, Moidur Rahman, Marisennayya Senapathy

Bibliographic record

VenueInternational Journal of Business Data Communications and Networking · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsnot available
FundersDeanship of Scientific Research, Prince Sattam bin Abdulaziz UniversityCanadian Centre for Applied Research in Cancer ControlUniwersytet Przyrodniczy w PoznaniuPrince Sattam bin Abdulaziz University
KeywordsComputer scienceWirelessWireless networkComputer securityTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a comprehensive survey of security needs, applications, and current challenges and threats for 6G wireless communication networks. 6G technology has brought much attention to business entities and academia recently. The development of a relevant 6G wireless technology to meet the security issues and technical challenges of 5G networks as well as major system upgrades over previous wireless technologies are discussed. The importance of the comparative study is estimated for security issues and communication of devices like wireless devices and focuses on creative innovations that would offer the progression changes required for empowering 6G. First, the authors present the evolution and security threats landscape of wireless communication networks. Then they explore the potential applications of 6G networking technologies. Finally, this paper concludes with a detailed discussion of security issues, research challenges, and possible solutions in 6G that enable critical technologies.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.044
GPT teacher head0.296
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Business Data Communications and NetworkingSame topicAdvanced Wireless Communication TechnologiesFrench-language works237,207