2026· IEEE Open Journal of the Communications Society· Vol 7, pp. 8772-8785· 0 citations· 24 references
TL;DR
This study proposes an intelligent Q-learning-enhanced Evolutionary Game Theory (QEGT) routing mechanism for USNs that leverages game-theoretic incentives and Q-learning to adaptively select strategies.
Abstract
Unmanned Aerial Vehicle (UAV) swarm networks play a vital role as real-time communication relays. It provides communication services in applications such as disaster management, intelligent transport, and environmental monitoring. The inherent characteristics of Unmanned Swarm Networks (USNs), such as flexible deployment and high operational adaptability, make them valuable in environments with limited infrastructure. However, the highly dynamic and decentralized nature of USNs presents major challenges in designing efficient and reliable routing protocols. Traditional approaches often struggle with frequent topology changes and high mobility of USNs. To address these challenges, this study proposes an intelligent Q-learning-enhanced Evolutionary Game Theory (QEGT) routing mechanism for USNs. The proposed scheme leverages game-theoretic incentives and Q-learning to adaptively select strategies. The optimal next-hop UAV is selected based on residual energy, queue length, and proximity to the destination. Extensive simulations in NS-3 demonstrate the effectiveness of the proposed QEGT scheme. Simulation results show that the proposed QEGT scheme outperforms the state-of-the-art approaches in terms of network survival time, the number of successfully delivered packets, average hop count, and average delay.
Results show that topology‐aware cooperative learning can provide a scalable and practical solution for reliable UAV communication in future intelligent aerial and 6G‐enabled networks, particularly in dense deployments.
V. Nam, A. Chehri, Weiwei Jiang et al.· Expert systems· 0 citations
Major disasters such as earthquakes, floods, and wildfires can rapidly destroy terrestrial communication infrastructure, producing an extreme operating environment in which power, road, and network outages compound one another. Owing to their rapid deployability, flexible networking, and three-dimensional mobility, unmanned aerial vehicle (UAV) swarms are being studied as a flexible component of emergency communication systems. This paper reviews UAV swarm ad-hoc network communication technology for emergency scenarios. It examines the technical characteristics and applicability boundaries of three network architectures---flat, hierarchical clustering, and space-air-ground integrated---and surveys recent advances in routing and medium access, intelligent networking optimization, and transmission and security assurance. Particular attention is given to the reported performance and applicability of emerging approaches, including reinforcement-learning-based adaptive routing, decentralized federated learning, digital twins, and semantic communication, under highly dynamic and resource-constrained conditions. Drawing on studies of emergency routing, post-disaster data collection, semantic forwarding, and multi-layer coverage, the paper assesses current validation methods and outlines research directions in energy use, scalability, security, resilience, and standardization. Its contribution is a cross-layer comparison that relates architecture choices to protocol requirements, implementation costs, and validation maturity.
Yihang Ren, Huatao Zhu, Jie Zhang· International Journal of Eme...· 0 citations
The results confirm that the integration of artificial intelligence, energy-aware routing, and UAV trajectory optimization provides an effective and scalable solution for next-generation UAV-assisted IoT systems and establishes a robust foundation for intelligent 6G-enabled wireless sensor networks.
Mojtaba Nasehi· Internet of Things and Cloud...· 0 citations
An in-depth review of energy-efficient routing protocols that have been developed for FANETs and highlights the main research challenges, such as high mobility, dynamic topology, routing overhead, scalability, and security, and discusses future research directions to design more intelligent and energy-aware routing protocols.
Ragvinder Kaur, Amit Sharma· Journal of Intelligent Decis...· 0 citations
The Enhanced RDAP (e-RDAP), a multi-criteria association policy that combines RSSI, Packet Delivery Ratio (PDR), and communication delay with an adaptive deployment strategy is introduced, indicating that QoS-aware multi-criteria association provides additional gains beyond load-aware association alone.
Lucas Baptista de Moraes, N. Fernandes, Fernanda G. O. Passos et al.· Annals of Telecommunications· 0 citations
The adoption of a new communication paradigm is getting attention in the research world, where Flying Ad Hoc Networks (FANETs) have been deemed a viable approach for supporting coordinated operations of multiple Unmanned Aerial Vehicles (UAVs) in situations characterized by dynamic environments and the absence of infrastructure. Taking into consideration these drawbacks, in this paper, a novel and up-to-date AI-Based Mobility and Topology Management Framework for Flying Ad Hoc Networks via Hybrid Bio-Inspired Optimization is proposed. The proposed systems combine a Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) inspired model, introducing a novel hybrid model, with Artificial Intelligence techniques to provide a dynamic framework for optimizing UAV mobility patterns, topology formation, and communication paths within the proposed framework. Predictive mobility analysis using AI to make networks more adaptable and minimize topology changes. In addition, the hybrid optimization method will optimize the routing efficiency, reduce the communication overhead, and increase the packet delivery efficiency between nodes in the highly dynamic FANET environment. Results of experimental analysis prove that the proposed scheme has a better PDR of 96.4%, lower EED or end-to-end delay of 31%, and better topology stability that performs better than the traditional mobility management approaches with respect to reducing energy consumption.
Anshu Vashisth, Gagandeep Kaur, Ruhi Saxena et al.· 2026 7th International Confe...· 0 citations