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

This paper considers an unmanned aerial vehicle (UAV)-aided millimeter Wave (mmWave) multiple-input-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 three-dimensional (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.

Automated summary

This paper proposes a UAV-aided mmWave MIMO NOMA system to provide wireless access services for IoT devices, aiming to maximize the downlink sum rate through joint optimization of UAV placement, beam pattern, and transmit power. The optimal UAV placement and beam pattern synthesis are achieved using convex optimization techniques and MOEA/D algorithm, while a suboptimal algorithm based on FP is proposed to achieve near-optimal performance. Numerical results demonstrate a significant performance gain compared to OFDMA scheme in terms of sum rate for all IoT devices.