Adaptive AI-Based Algorithms for Optimizing Communications Across Network Layers of Dynamic Flying Ad Hoc Networks
में बचाया:
| में प्रकाशित: | ProQuest Dissertations and Theses (2025) |
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ProQuest Dissertations & Theses
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| ऑनलाइन पहुंच: | Citation/Abstract Full Text - PDF |
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| 100 | 1 | |a He, Linsheng | |
| 245 | 1 | |a Adaptive AI-Based Algorithms for Optimizing Communications Across Network Layers of Dynamic Flying Ad Hoc Networks | |
| 260 | |b ProQuest Dissertations & Theses |c 2025 | ||
| 513 | |a Dissertation/Thesis | ||
| 520 | 3 | |a 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. | |
| 653 | |a Engineering | ||
| 653 | |a Computer engineering | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Communication | ||
| 653 | |a Electrical engineering | ||
| 773 | 0 | |t ProQuest Dissertations and Theses |g (2025) | |
| 786 | 0 | |d ProQuest |t ProQuest Dissertations & Theses Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3213695015/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3213695015/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |