Non-Orthogonal Multiple Access for Air-to-Ground Communication

Abstract

This paper investigates ground-aerial uplink non-orthogonal multiple access (NOMA) cellular networks. A rotary-wing unmanned aerial vehicle (UAV) user and multiple ground users (GUEs) are served by ground base stations (GBSs) by utilizing the uplink NOMA protocol. The UAV is dispatched to upload specific information bits to each target GBSs. Specifically, our goal is to minimize the UAV mission completion time by jointly optimizing the UAV trajectory and UAV-GBS association order while taking into account the UAV's interference to non-associated GBSs. The formulated problem is a mixed integer non-convex problem and involves infinite variables. To tackle this problem, we efficiently check the feasibility of the formulated problem by utilizing graph theory and topology theory. Next, we prove that the optimal UAV trajectory needs to satisfy the \emph{fly-hover-fly} structure. With this insight, we first design an efficient solution with predefined hovering locations by leveraging graph theory techniques. Furthermore, we propose an iterative UAV trajectory design by applying successive convex approximation (SCA) technique, which is guaranteed to coverage to a locally optimal solution. We demonstrate that the two proposed designs exhibit polynomial time complexity. Finally, numerical results show that: 1) the SCA based design outperforms the fly-hover-fly based design; 2) the UAV mission completion time is significantly minimized with proposed NOMA schemes compared with the orthogonal multiple access (OMA) scheme; 3) the increase of GUEs' quality of service (QoS) requirements will increase the UAV mission completion time.

References in corpus (9)

• Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges
• Unmanned Aerial Vehicle with Underlaid Device-to-Device Communications: Performance and Tradeoffs
• Placement Optimization of UAV-Mounted Mobile Base Stations
• Cooperative Non-Orthogonal Multiple Access with Simultaneous Wireless Information and Power Transfer
• Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management
• A Mathematical Proof of the Superiority of NOMA Compared to Conventional OMA
• Uplink Cooperative NOMA for Cellular-Connected UAV
• Cellular Connectivity for UAVs: Network Modeling, Performance Analysis and Design Guidelines
• Coexistence of Terrestrial and Aerial Users in Cellular Networks

Cited by in corpus (6)

• Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G
• Energy-Constrained UAV Data Collection Systems: NOMA and OMA
• CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks
• Learning-Based UAV Trajectory Optimization with Collision Avoidance and Connectivity Constraints
• Channel State Acquisition in Uplink NOMA for Cellular-Connected UAV: Exploitation of Doppler and Modulation Diversities
• Multi-Agent Reinforcement Learning in NOMA-aided UAV Networks for Cellular Offloading