Uplink Noma in UAV-Assisted IoT Networks

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dc.contributor.author Mrad, Ali
dc.date.accessioned 2022-07-22T09:00:03Z
dc.date.available 2022-07-22T09:00:03Z
dc.date.copyright 2022 en_US
dc.date.issued 2022-05-17
dc.identifier.uri http://hdl.handle.net/10725/13857
dc.description.abstract Non-orthogonal multiple access (NOMA) is one of the promising access technologies to improve spectral efficiency and serve a higher number of users in different internet of things (IoT) systems. This technology proves important in scenarios with time-sensitive services when data has to be collected before a set deadline, otherwise, it is rendered useless, as well as, in scenarios with limited resources and large number of users. Therefore, this thesis explores the potential of NOMA in improving the performance of IoT networks served by unmanned aerial vehicles (UAVs). The first part of the thesis considers the problem of data collection from time-constrained IoT devices through deploying a UAV with uplink NOMA. This problem is formulated to determine an optimized UAV trajectory, IoT devices scheduling, and power allocation in the NOMA clusters that maximize the number of served devices while considering various constraints including the energy and flight duration of the UAV and successive interference cancellation (SIC) in the NOMA cluster. Given the complexity of the problem and the incomplete knowledge about the environment, the problem is divided into two subproblems: the first models the UAV trajectory and the selection of the first device in the NOMA cluster at each time slot as a Markov Decision Process, and uses Proximal Policy Optimization to solve it. The second device is then selected using a heuristic algorithm based on prioritizing devices with higher bit rate requirements and strict deadlines. The second subproblem addresses power allocation inside the NOMA cluster, and is formulated as an optimization problem for maximizing the sum rates of the two selected users. Regarding the second part of the thesis, uplink NOMA with joint-transmission coordinated multi-point (JT-CoMP) is leveraged in a UAV-assisted IoT network. IoT devices with strong channel conditions utilize NOMA to transmit to a single UAV closest to each device, while the IoT device with poor channel conditions utilize JT-CoMP NOMA and transmits to two UAVs. This problem is formulated as an optimization problem to maximize the sum rate of the IoT devices given the NOMA, UAV, and IoT devices constraints. The obtained problem is non-convex mixed-integer non-linear program which is difficult to solve in a straightforward manner, hence alternating optimization technique is used where the original problem is divided into two subproblems. In the first subproblem the positions of the UAVs are optimized to maximize the sum rate of the IoT devices and the second subproblem handles IoT devices transmit power optimization then alternating between the two subproblems is performed to improve the performance. For each subproblem, successive convex approximation is leveraged to get a solution. Then, simulation results are presented to demonstrate the performance gains of the proposed solutions ascompared to alternative solution approaches. en_US
dc.language.iso en en_US
dc.subject Uplink Noma in UAV-Assisted IoT Networks en_US
dc.subject Internet of things en_US
dc.subject Computer networks en_US
dc.subject Drone aircraft en_US
dc.subject Lebanese American University -- Dissertations en_US
dc.subject Dissertations, Academic en_US
dc.title Uplink Noma in UAV-Assisted IoT Networks en_US
dc.type Thesis en_US
dc.term.submitted Spring en_US
dc.author.degree MS in Computer Science en_US
dc.author.school SAS en_US
dc.author.idnumber 201705188 en_US
dc.author.commembers Haraty, Ramzi
dc.author.commembers Abbas, Nadine
dc.author.department Computer Science And Mathematics en_US
dc.description.physdesc 1 online resource (xi, 66 leaves): col. ill. en_US
dc.author.advisor Sharafeddine, Sanaa
dc.author.advisor Assi, Chadi
dc.keywords Non-orthogonal multiple access (NOMA) en_US
dc.keywords Deep reinforcement learning (DRL) en_US
dc.keywords Internet of things (IoT) en_US
dc.keywords Unmanned Aerial Vehicle (UAV) en_US
dc.keywords Timely data collection en_US
dc.keywords Joint-Transmission Coordinated Multi-Point (JT-CoMP) en_US
dc.description.bibliographiccitations Bibliography: leaf 61-66. en_US
dc.identifier.doi https://doi.org/10.26756/th.2022.383
dc.author.email ali.mrad03@lau.edu en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php en_US
dc.publisher.institution Souad Hasbany en_US
dc.author.affiliation Lebanese American University en_US

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