Cellular networks based on new generation standards are the major enabler for Internet of things (IoT) communication. Narrowband-IoT and Long Term Evolution for Machines are the newest wide area network-based cellular technologies for IoT applications. The deployment of unmanned aerial vehicles (UAVs) has gained the popularity in cellular networks by using temporary ubiquitous coverage in the areas where the infrastructure-based networks are either not available or have vanished due to some disasters. The major challenge in such networks is the efficient UAVs deployment that covers maximum users and area with the minimum number of UAVs. The performance and sustainability of UAVs is largely dependent upon the available residual energy especially in mission planning. Although energy harvesting techniques and efficient storage units are available, but these have their own constraints and the limited onboard energy still severely hinders the practical realization of UAVs. This paper employs neglected parameters of UAVs energy consumption in order to get actual status of available energy and proposed a solution that more accurately estimates the UAVs operational airtime. The proposed model is evaluated in test bed and simulation environment where the results show the consideration of such explicit usage parameters achieves significant improvement in airtime estimation.

基于新一代标准的蜂窝网络是物联网（IoT）通信的主要推动力。窄带物联网和机器的长期演进是用于物联网应用的最新的基于广域网的蜂窝技术。通过在基于基础设施的网络不可用或由于某些灾难而消失的区域中使用临时的普遍覆盖，无人飞行器（UAV）的部署已在蜂窝网络中得到普及。这种网络的主要挑战是有效的无人机部署，需要以最少的数量覆盖最大的用户和区域。无人机的性能和可持续性在很大程度上取决于可用的剩余能量，尤其是在任务计划中。尽管可以使用能量收集技术和高效的存储单元，但是这些都有其自身的限制，并且机载能量有限仍然严重阻碍了无人机的实际实现。为了获得可用能量的实际状态，本文采用了被忽略的无人机能耗参数，并提出了一种可以更准确地估计无人机运行时间的解决方案。在试验台和仿真环境中对提出的模型进行了评估，结果表明，考虑使用这些明确的使用参数可以显着改善通话时间估计。