Joint 3D Trajectory and Power Optimization for UAV-Aided mmWave MIMO-NOMA Networks

Abstract

This paper considers an unmanned aerial vehicle (UAV)-aided millimeter Wave (mmWave) multipleinput-multiple-output (MIMO) non-orthogonal multiple access (NOMA) system, where a UAV serves as a flying base station (BS) to provide wireless access services to a set of Internet of Things (IoT) devices in different clusters. We aim to maximize the downlink sum rate by jointly optimizing the threedimensional (3D) placement of the UAV, beam pattern and transmit power. To address this problem, we first transform the non-convex problem into a total path loss minimization problem, and hence the optimal 3D placement of the UAV can be achieved via standard convex optimization techniques.Then, the multiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm is presented for the shaped-beam pattern synthesis of an antenna array. Finally, by transforming the original problem into an optimal power allocation problem under the fixed 3D placement of the UAV and beam pattern, we derive the closed-form expression of transmit power based on Karush-Kuhn-Tucker (KKT) conditions. In addition, inspired by fraction programming (FP), we propose a FP-based suboptimal algorithm to achieve a near-optimal performance. Numerical results demonstrate that the proposed algorithm achieves a significant performance gain in terms of sum rate for all IoT devices, as compared with orthogonal frequency division multiple access (OFDMA) scheme.

Energy-Efficiency Optimization for D2D Communications Underlaying UAV-Assisted Industrial IoT Networks With SWIPT

“…Based on the previous subsections, the complete iterative algorithm for problem (13) is summarized in TABLE I. To simplify the description, let…”

“…In [12], the authors further considered the UAV-assisted wireless power transfer system, and maximized the sum received power of all devices by the successive convex programming-based trajectory design method. In [13], a sum rate maximization problem was investigated in a UAVaided mmWave network, where the 3D deployment of UAV, power allocation and beam pattern were considered. In [14], a secrecy rate optimization problem was studied in a secure UAV-assisted SWIPT network, and solved by an alternative optimization method.…”

Joint position and trajectory optimization of flying base station in 5G cellular networks, based on users' current and predicted location

“…The purpose of this paper is to minimize the power of the entire UAV. In [19] writers transform the nonconvex problem into an efficient power allocation problem for UAV 3D placement.…”

“…Each drone focuses on its active users and assuming that there are no other neighboring drones, it calculates the SNR according to the location of its active users and it moves in the direction in which the maximum SNR is average, hence it improves the low-density drone spectral efficiency of the low-altitude. [19] propose a method for maximization of the sum-rate in mmW networks. To aim this goal, they jointly optimized UAV location in 3D space, beam pattern, and transmit power.…”

Spectral-efficient hybrid precoding for multi-antenna multi-user mmWave massive MIMO systems with low complexity

“…Furthermore, the small wavelength and narrow beam characteristics of millimeter waves allow systems to employ large-scale antenna arrays [4], which can be packed into small-form factors and achieve reasonable array gains. Therefore, the combination of mmWave and massive MIMO systems can effectively realize the complementary advantages of the two technologies [5][6][7][8].…”