Enhancing UAV Network Efficiency through 6G+ Enabled Federated Learning Algorithms and Energy optimization Techniques

Andreas Andreou, Constandinos X. Mavromoustakis, Jordi Mongay Batalla, Evangelos Markakis, Athina Bourdena, George Mastorakis, Houbing Song

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

Abstract

This study presents an innovative approach to enhancing the efficiency of Unmanned Aerial Vehicles (UAV) in IoT networks. Employing UAVs as flying relays focuses on their role in data collection and support for terrestrial cellular networks. The central innovation lies in the application of Federated Learning (FL), which processes data while ensuring user privacy and reducing communication overhead. Addressing the challenge of UAVs' limited battery life, which restricts sustained FL operations, we introduce the Enhanced UAV Network optimization Algorithm with Adaptive Spatial Play (ENUO-ASP). ENUOASP incorporates a modified Particle Swarm optimization (PSO) technique to determine optimal UAV placements, enhancing data collection by focusing on the Signal-to-Interference Ratio (SINR). Additionally, the paper utilizes the Deep Deterministic Policy Gradient (DDPG) method for dynamic resource allocation, optimizing energy consumption and reducing link latency between the UAV network and users. The findings indicate that the ENUO algorithm outperforms existing methods by achieving higher data rates and balanced SINR. Furthermore, the ASP resource allocation strategy improves FL execution, significantly lowering latency and energy use. This research contributes to the UAV-enabled communication field, offering a more efficient and performance-driven solution for advanced IoT applications.

Original languageEnglish
Title of host publication20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages192-197
Number of pages6
ISBN (Electronic)9798350361261
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event20th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2024 - Hybrid, Ayia Napa, Cyprus
Duration: 27 May 202431 May 2024

Publication series

Name20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024

Conference

Conference20th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2024
Country/TerritoryCyprus
CityHybrid, Ayia Napa
Period27/05/2431/05/24

Keywords

  • deep RL
  • Federated Learning
  • IoT
  • Network Coverage optimization
  • Resource Allocation
  • UAV

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