Kieu-Xuan, T.; Le-Thi, A. UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization. J. Sens. Actuator Netw.2024, 13, 18.
Kieu-Xuan, T.; Le-Thi, A. UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization. J. Sens. Actuator Netw. 2024, 13, 18.
Kieu-Xuan, T.; Le-Thi, A. UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization. J. Sens. Actuator Netw.2024, 13, 18.
Kieu-Xuan, T.; Le-Thi, A. UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization. J. Sens. Actuator Netw. 2024, 13, 18.
Abstract
Utilizing unmanned aerial vehicles (UAVs) to facilitate wireless communication has emerged as a viable and promising strategy aimed at enhancing both current and prospective wireless systems. This approach offers many advantages by establishing line-of-sight connections, optimizing operational efficiency, and enabling flexible deployment capabilities in various terrains. Thus, in this paper, we investigate UAV communication in a relaying network in which a UAV helps communication between a source and two destination users while flying to a location. To have a complete view of our proposed system, we consider both orthogonal multiple access as OFDM and non-orthogonal multiple access (NOMA) scenarios. Moreover, we apply successive convex optimization (SCO) and the Block-coordinate gradient descent (BCGD) for the sum-rate optimization problems to improve the system performance under constraints of total bandwidth and total power at the ground base station and UAV. The experimental results validate that the achievable secrecy rates are notably enhanced by using our proposed algorithms and show optimal trends for critical parameters, such as transmit powers, the flight trajectory and speed of UAV, and resource allocation of OFDM and NOMA.
Keywords
UAV-NOMA; UAV-OFDM; Successive convex optimization SCO; Sum data rate; Block-coordinate gradient descent BCGD.
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
