Experimental Evaluation of AoA Estimation for UAV to Massive MIMO

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dc.contributor.committeeMemberKnightly, Edward
dc.contributor.committeeMemberSabharwal, Ashutosh
dc.contributor.committeeMemberChi, Taiyun
dc.creatorRice, Tarence
dc.date.accessioned2023-06-13T15:53:34Z
dc.date.created2023-05
dc.date.issued2023-04-19
dc.date.submittedMay 2023
dc.date.updated2023-06-13T15:53:34Z
dc.descriptionEMBARGO NOTE: This item is embargoed until 2024-05-01
dc.description.abstractMassive MIMO (multiple-input, multiple-output) base stations are widely used for wireless networks to deploy multiple antennas, increasing their quality, throughput, and radio link capacity. Unmanned aerial vehicles (UAV) are prevalent due to their low cost and ease of use. Unmanned aerial vehicles (UAV) are prevalent due to their low cost and ease of use, allowing for multiple use cases that provide telemetry information to civilian, commercial, and military applications. In particular, we implement a suite of Angle of Arrival (AoA) estimation algorithms exploring their performance for UAV communication networks. From the evaluation of the five AoA estimations, Beamscan offers a spatial, spectral response that enables us to analyze both secondary propagation paths and the most likely AoA, providing us with a complete picture of the environment. We discovered with convergence time that when under-sampled, the AoA estimator detects the multi-path with a higher normalized power, impacting the AoA estimate result. We estimated azimuth AoA via horizontal subarrays and its effects on the multi-path AoA estimates for hovering drones. We discovered the effects of Rice football stadium seats as we decreased the number of antennas. We find that when evaluating hovering drones' azimuth and elevation AoA estimation, elevation estimation yields a median error of 13.8\degree higher error than azimuth for the 5x5 antenna scenario. Evaluated was the performance of the 2-D Beamscan spatial spectrum estimator. It provides higher accuracy between the two different channels of azimuth and elevation. This work will inform system designers on specifications from AoA estimations when designing a Massive MIMO to drone network.
dc.embargo.lift2024-05-01
dc.embargo.terms2024-05-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationRice, Tarence. "Experimental Evaluation of AoA Estimation for UAV to Massive MIMO." (2023) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/114906">https://hdl.handle.net/1911/114906</a>.
dc.identifier.urihttps://hdl.handle.net/1911/114906
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectDrone
dc.subjectUnmanned Air Vehicles
dc.subjectAngle of Arrival
dc.subjectLocalization
dc.subjectMassive MIMO
dc.titleExperimental Evaluation of AoA Estimation for UAV to Massive MIMO
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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