This paper presents a distributed graph neural network (GNN) framework for anti-jamming in large-scale IoT systems with dynamic interference and strict energy constraints. The proposed approach...

Author: Hue Tran Thi

Keyword: Distributed graph neural networks Anti-jamming communications Internet of Things Energy-efficient networking Scalable wireless networks

This paper proposes a GNN-enhanced multi-agent deep reinforcement learning framework for antijamming routing in mobile ad hoc networks. The approach combines temporal graph representations with...

Author: Hanh Vu My, Oanh Le Thi Kieu

Keyword: MANET Anti-jamming Graph Neural Networks (GNN) Multi-Agent Reinforcement Learning (MARL) Adversarial Learning

This paper studies joint power control and spectrum access in dynamic flying ad hoc networks (FANETs) under co-channel interference and adaptive jamming. We propose a graph neural network-aided...

Author: Dung Nguyen Thi

Keyword: FANET Multi-agent reinforcement learning Graph neural networks Anti-jamming Resource optimization

Mobile ad hoc networks (MANETs) operating in hostile environments are vulnerable to coordinated wireless, routing, trust, and topology attacks. This paper proposes a tri-level adversarial GNN–DRL...

Author: Hoan Tran Quoc

Keyword: Mobile ad-hoc networks Adversarial graph neural networks Trust-aware graph recovery Hierarchical deep reinforcement learning Self-play learning.