Content area

Abstract

Dynamic Flying Ad Hoc Networks (FANET) have emerged as a prominent research area due to the innovation, development, and widespread adoption of drone terminal devices. The increasing diversity of FANETs has introduced new demands and challenges for airborne communications, particularly in the lower layers of the Open Systems Interconnection (OSI) communication model. This study begins by clarifying the research context and providing relevant definitions. It then outlines the key challenges and limitations of traditional methods. It is followed by optimizing the FANET communication across three critical dimensions: high transmission data rate communication, decentralized distributed high-sensing communication, and adaptive dynamic high-mobility communication.

While Terahertz (THz) links can achieve data transmission rates exceeding 100 Gigabits per Second (Gbps), they are highly susceptible to obstacles and require narrow, highly directional beams to concentrate signal radiation. To address this, this dissertation proposes a comprehensive Terahertz airborne network (TAN) media access control (MAC) protocol that facilitates dynamic FANET networks with resilient, smooth, and high-rate links. Moreover, Directional Antennas (DA), though vital in FANETs, are limited by their inability to exchange messages as frequently as Omnidirectional Antennas (OA) to sense the surrounding environment. To overcome this, this study introduces a Distributed Adaptive Layer (DAL) protocol between the MAC and Physical (PHY) layers. DAL enables each node to interact with the environment only using local observations, avoiding coordinator participation and reducing communication delay while maintaining high throughput. Additionally, the diverse flight speeds and the associated Doppler effect significantly impact FANET performance. To mitigate this, this work implements the Doppler Adaptive Waveform Engine (DAWE) protocol, which adjusts node modulation methods and parameters, responding to the time series highly dynamic environment in FANET. This approach reduces deployment complexity and improves Bit Error Rates (BER).

Overall, this dissertation presents multiple protocols for offering a comprehensive framework for optimizing FANET communications, demonstrating the effective applications of advanced computational algorithms to complex, real-world network scenarios, and paving the way for more efficient and reliable deployment of FANETs.

Details

1010268
Business indexing term
Title
Adaptive AI-Based Algorithms for Optimizing Communications Across Network Layers of Dynamic Flying Ad Hoc Networks
Number of pages
166
Publication year
2025
Degree date
2025
School code
0004
Source
DAI-A 86/11(E), Dissertation Abstracts International
ISBN
9798315766780
Advisor
Committee member
Kumar, Sunil; Song, Aijun; Hong, Xiaoyan; Sun, Shunqiao
University/institution
The University of Alabama
Department
Electrical and Computer Engineering
University location
United States -- Alabama
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
31557801
ProQuest document ID
3213695015
Document URL
https://www.proquest.com/dissertations-theses/adaptive-ai-based-algorithms-optimizing/docview/3213695015/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic