Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV’s co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

中文翻译：

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NOMA蜂窝连接无人机网络的上行预编码优化

无人机 (UAV) 由于其成本效益和灵活部署，在无线网络中发挥着重要作用。特别是，将无人机集成到现有蜂窝网络中具有提供高速率和超可靠通信的巨大潜力。在本文中，我们研究了蜂窝网络中从使用非正交多址 (NOMA) 的无人机以及从地面用户到基站 (BS) 的上行链路传输。具体来说，我们的目标是通过优化多天线无人机的预编码向量，最大化从 UAV 到特定频段中的 BS 以及从 UAV 的同信道用户到其相关 BS 的上行链路总速率。为了减轻干扰，我们不仅对 UAV 连接的 BS 应用了连续干扰消除 (SIC)，但也适用于同一频段内与地面用户相关的基站。提出了对 SIC 解码和传输速率要求有约束的预编码优化问题，该问题是非凸的。因此，我们引入辅助变量并应用基于一阶泰勒展开的近似值将其转换为二阶锥规划。相应地，设计了一种迭代算法来获得低复杂度问题的解决方案。给出了数值结果以证明我们提出的方案的有效性。我们引入辅助变量并应用基于一阶泰勒展开的近似值将其转换为二阶锥规划。相应地，设计了一种迭代算法来获得低复杂度问题的解决方案。给出了数值结果以证明我们提出的方案的有效性。我们引入辅助变量并应用基于一阶泰勒展开的近似值将其转换为二阶锥规划。相应地，设计了一种迭代算法来获得低复杂度问题的解决方案。给出了数值结果以证明我们提出的方案的有效性。