Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks
As sixth-generation (6G) networks move toward ultra-dense, intelligent edge environments, efficient resource management under stringent privacy, mobility, and energy constraints becomes critical. This paper introduces a novel Federated Multi-Agent Rei
Authors
- Qi Min (ORCID: https://orcid.org/0000-0002-8557-4139)
- Francisco Javier Esono Nkulu Andong
Institutions
- Northwestern Polytechnical University (CN)
- Northwestern Polytechnic University (US)
Publication Details
- Published
- 2025-09-19
- DOI
- https://doi.org/10.36227/techrxiv.175825722.26190757/v1
- Citations
- 1
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 2.48