Optimized Coordinated Resource Allocation and Power Control for Wireless Communication Networks

Lucky Oghenechodja Daniel, Ghanshyam Singh, Daniel Mashao, Peter Olukanmi

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

Abstract

This paper investigates an optimized approach to coordinated resource allocation and power control for wireless communication networks. To address limitations in existing methods, such as scalability and fairness, a novel algorithm is implemented that leverages federated learning regression-based decision trees to achieve efficient resource allocation and improved network performance. The system model considers a dense communication network with different user equipment types and incorporates constraints like power limitations and quality of service requirements. Simulation results demonstrate that the implemented approach significantly outperforms existing techniques in terms of throughput, energy efficiency, and latency.

Original languageEnglish
Title of host publication7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024 - Proceedings
EditorsSameerchand Pudaruth, Upasana Singh
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350387902
DOIs
Publication statusPublished - 2024
Event7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024 - Port Louis, Mauritius
Duration: 1 Aug 20242 Aug 2024

Publication series

Name7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024 - Proceedings

Conference

Conference7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024
Country/TerritoryMauritius
CityPort Louis
Period1/08/242/08/24

Keywords

  • Decision Trees
  • Federated Learning
  • Power Control
  • Resource Allocation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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