An adaptive and reliable forward error correction mechanism for real-time video delivery from UAVs

Sarvi, Batoul

An adaptive and reliable forward error correction mechanism for real-time video delivery from UAVs

dc.contributor.advisor	Sreenan, Cormac J.
dc.contributor.advisor	Zahran, Ahmed
dc.contributor.author	Sarvi, Batoul
dc.contributor.funder	Science Foundation Ireland
dc.date.accessioned	2024-05-29T09:03:50Z
dc.date.available	2024-05-29T09:03:50Z
dc.date.issued	2023
dc.date.submitted	2023
dc.description.abstract	This thesis introduces the Adaptive and Reliable Forward Error Correction (AR-FEC) mechanism, an advanced protocol designed to enhance real-time video transmission in Unmanned Aerial Vehicles (UAVs) communications. Addressing the challenge of unreliable wireless channels, AR-FEC leverages edge computing principles at the application layer to incorporate adaptive FEC, dynamic video quality, and Unequal Error Protection (UEP). By dynamically adjusting redundancy frames within each video Group of Pictures (GoP) based on packet loss, round-trip times, and cross-layer network information, AR-FEC optimizes the balance between video quality and transmission reliability. A significant portion of this work is dedicated to rigorous simulation-based validation using the NS3 network simulator. The simulation environment is carefully crafted to replicate a range of UAV operational conditions, including varying distances and network loads, to assess the AR-FEC protocol's performance under realistic scenarios. Key performance indicators such as deliverable frame count, latency, throughput, and real-time streaming constraints are meticulously evaluated, demonstrating AR-FEC's capacity to outperform existing error correction methods significantly. The simulations also explore the protocol's behavior with multiple UAVs as senders, highlighting its robustness in complex network settings. The results indicate a marked improvement in video delivery quality, showcasing AR-FEC's potential for broad application across different UAV uses, from surveillance to disaster management. In summary, the thesis articulates the development and validation of AR-FEC, illustrating its superior performance and adaptability. The proposed mechanism not only advances the field of UAV communication but also establishes a comprehensive simulation framework for future research, potentially guiding the development of more reliable and efficient UAV multimedia communication systems.	en
dc.description.status	Not peer reviewed	en
dc.description.version	Accepted Version	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Sarvi Ghamsari, B. 2023. An adaptive and reliable forward error correction mechanism for real-time video delivery from UAVs. MSc Thesis, University College Cork.
dc.identifier.endpage	96
dc.identifier.uri	https://hdl.handle.net/10468/15942
dc.language.iso	en	en
dc.publisher	University College Cork	en
dc.relation.project	info:eu-repo/grantAgreement/SFI/SFI Centres for Research Training Programme::Data and ICT Skills for the Future/18/CRT/6222/IE/SFI Centre for Research Training in Advanced Networks for Sustainable Societies/
dc.rights	© 2023, Batoul Sarvi Ghamsari.
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	UAV
dc.subject	Error correction
dc.subject	Multimedia communication
dc.subject	FEC
dc.subject	Video streaming
dc.title	An adaptive and reliable forward error correction mechanism for real-time video delivery from UAVs
dc.type	Masters thesis (Research)	en
dc.type.qualificationlevel	Masters	en
dc.type.qualificationname	MSc - Master of Science	en