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.