Optimized Coordinated Resource Allocation and Power Control for Wireless Communication Networks

被引:0
作者
Daniel, Lucky Oghenechodja [1 ]
Singh, Ghanshyam [1 ]
Mashao, Daniel [1 ]
Olukanmi, Peter [1 ]
机构
[1] Univ Johannesburg, Dept Elect & Elect Engn Sci, Johannesburg, South Africa
来源
2024 7TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, BIG DATA, COMPUTING AND DATA COMMUNICATION SYSTEMS, ICABCD 2024 | 2024年
关键词
Resource Allocation; Power Control; Decision Trees; Federated Learning;
D O I
10.1109/ICABCD62167.2024.10645229
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:10
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