International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 1 (January-February 2025) Submit your research before last 3 days of February to publish your research paper in the issue of January-February.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 1
January-February 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

AI-Driven Network Supervision in 6G Enhancing Self-Association, Optimization, and Self-governing Maintenance

Author(s) Rakhi Sachin Punwatkar
Country India
Abstract The advent of 6G networks is expected to transfigure communication by providing ultra-high speeds, low latency, and omnipresent connectivity. One of the central challenges in 6G is well-organized network management, specifically as the scale and complexity of the network grow. This paper explores the role of Artificial Intelligence (AI) and Machine Learning (ML) in 6G network design, concentrating on their application in network self-organization, optimization, and analytical maintenance. By utilizing AI-driven algorithms, 6G networks can separately manage resources, optimize presentation, and predictively address faults before they interrupt services. The paper discusses the implementation of AI technologies in network resource allocation, real-time traffic management, fault detection, and automated retrieval mechanisms, prominence both the opportunities and challenges associated with these innovations. The proposed approach aims to establish a more resilient, adaptive, and effectual network capable of meeting the demands of upcoming generations.
Keywords AI, Machine Learning, 6G, Network Organization, Analytical Maintenance, Self-governing Network
Field Engineering
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-01-30
Cite This AI-Driven Network Supervision in 6G Enhancing Self-Association, Optimization, and Self-governing Maintenance - Rakhi Sachin Punwatkar - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.36195
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.36195
Short DOI https://doi.org/g83xxv
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com