Deploying uncrewed aerial vehicles (UAVs) as aerial base stations (BSs) to assist terrestrial connectivity has drawn significant attention in recent years. Alongside other UAV types, drones can be rapidly deployed in the air to bring Internet access to a region when serving users via terrestrial BSs is not feasible. Despite the numerous advantages of Drone-BSs, they pose several major challenges that need to be addressed in order to offer a stable drone-assisted wireless network service. Optimal placement of Drone-BSs dynamically in the air and moving them to ensure maximum coverage is among the most critical challenges. In this article, we present a comprehensive tutorial on 3D location optimization of Drone-BSs. We first introduce UAV-assisted wireless networks along with their use cases and associated challenges. We move towards 3D location optimization of Drone-BSs, as one of the most important challenges, and present a detailed review of the state-of-the-art techniques in the literature that can tackle this challenge. Starting with the conventional solutions to 3D placement of Drone-BSs, we review the existing artificial intelligence (AI)-based solutions to address this problem following upon the presentation of the AI techniques that are used by the existing studies on Drone-BSs placement.

近年来，部署无人驾驶飞行器 (UAV) 作为空中基站 (BS) 以协助地面连接已引起广泛关注。与其他无人机类型一起，当通过地面基站为用户提供服务不可行时，无人机可以快速部署在空中，为某个地区提供互联网接入。尽管 Drone-BS 具有众多优势，但它们提出了几个需要解决的主要挑战，以便提供稳定的无人机辅助无线网络服务。在空中动态优化无人机基站并移动它们以确保最大覆盖范围是最关键的挑战之一。在本文中，我们提供了一个关于 Drone-BS 的 3D 位置优化的综合教程。我们首先介绍无人机辅助无线网络及其用例和相关挑战。我们将无人机 BS 的 3D 位置优化作为最重要的挑战之一，并详细回顾了文献中可以应对这一挑战的最先进技术。从无人机 BS 的 3D 放置的传统解决方案开始，我们回顾了现有的基于人工智能 (AI) 的解决方案，以解决这个问题，然后介绍现有的无人机 BS 放置研究使用的 AI 技术。