Network Slicing for Mitigating Interference in Dense Deployments

Lucky O. Daniel, Daniel Mashao, Peter Olukanmi, Ghanshyam Singh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we have explored network slicing techniques to mitigate interference among the users in dense deployments of future generation communication networks. For this purpose, a novel algorithm that leverages federated generative adversarial networks is proposed. The simulation results demonstrate that the proposed approach significantly differs from existing techniques and has significant contribution in terms of offering a new approach to interference management that differs from existing literature.

Original languageEnglish
Title of host publication2025 IEEE 3rd Wireless Africa Conference, WAC 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331517588
DOIs
Publication statusPublished - 2025
Event3rd IEEE Wireless Africa Conference, WAC 2025 - Pretoria, South Africa
Duration: 24 Feb 202525 Feb 2025

Publication series

Name2025 IEEE 3rd Wireless Africa Conference, WAC 2025 - Proceedings

Conference

Conference3rd IEEE Wireless Africa Conference, WAC 2025
Country/TerritorySouth Africa
CityPretoria
Period24/02/2525/02/25

Keywords

  • Generalized Adversarial Networks
  • Interference. Federated Learning
  • Network Slicing

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Instrumentation
  • Development
  • Computer Networks and Communications
  • Hardware and Architecture
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Network Slicing for Mitigating Interference in Dense Deployments'. Together they form a unique fingerprint.

Cite this