Unmanned Aerial Vehicles (UAVs) are increasingly used to enable wireless communications. Due to their characteristics, such as the ability to hover and carry cargo, UAVs can serve as communications nodes, including Wi-Fi Access Points and Cellular Base Stations. In previous work, we proposed the Sustainable multi-UAV Performance-aware Placement (SUPPLY) algorithm, which focuses on the energy-efficient placement of multiple UAVs acting as Flying Access Points (FAPs). Additionally, we developed the Multi-UAV Energy Consumption (MUAVE) simulator to evaluate the UAV energy consumption, specifically when using the SUPPLY algorithm. However, MUAVE was initially designed to compute the energy consumption for rotary-wing UAVs only. In this paper, we propose eMUAVE, an enhanced version of the MUAVE simulator that allows the evaluation of the energy consumption for both rotary-wing and fixed-wing UAVs. Our energy consumption evaluation using eMUAVE considers reference and random networking scenarios. The results show that fixed-wing UAVs can be employed in the majority of networking scenarios. However, rotary-wing UAVs are typically more energy-efficient than fixed-wing UAVs when following the trajectories defined by SUPPLY.

翻译：无人机正日益广泛地应用于无线通信领域。凭借其悬停与载荷携带能力等特性，无人机可作为通信节点，包括Wi-Fi接入点和蜂窝基站。在先前工作中，我们提出了可持续多无人机性能感知部署算法，该算法专注于作为飞行接入点的多无人机能量高效部署。此外，我们开发了多无人机能耗仿真器，用于评估无人机能耗，特别是在使用SUPPLY算法时的能耗表现。然而，MUAVE最初仅设计用于计算旋翼无人机的能耗。本文提出eMUAVE——MUAVE仿真器的增强版本，可同时评估旋翼与固定翼无人机的能耗。我们基于eMUAVE的能耗评估涵盖了参考网络场景与随机网络场景。结果表明，固定翼无人机可适用于大多数网络场景，但在遵循SUPPLY定义的轨迹时，旋翼无人机通常比固定翼无人机更具能效优势。