About
Morad Mousa is a Researcher at Cranfield University's School of Aerospace, Transportation and Manufacturing. His academic journey includes a bachelor's degree in Electronics and Communications Engineering from the Higher Institute of Comprehensive - Alzahraa - Libya, and a master's in Networking from Sheffield Hallam University, where his thesis focused on routing protocols in networked environments. Currently pursuing a PhD under Prof. Saba Al-Rubaye, his research develops novel 5G NR-based approaches to enhance UAV positioning accuracy in urban areas, addressing challenges like NLOS errors and signal multipath effects.
His work integrates machine learning with 5G positioning signals to achieve sub-2m accuracy in urban environments. Key contributions include a neural network framework correcting 5G Time of Arrival (TOA) measurements, validated through MATLAB simulations of dense urban scenarios.
Publications include advancements in UAV positioning via 5G and neural networks, QoS measurements in aerial 5G trials, and foundational research on 5G NR-based UAV localization. His research bridges theoretical models with practical implementations, contributing to safer urban air mobility applications.
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