# Mobile Network Performance and Technical Feasibility of LTE-Powered Unmanned Aerial Vehicle
## 1 Introduction  
Unmanned aerial vehicles (UAVs), also known as drones, are becoming increasingly used in a wide variety of cases such as inspection, surveillance, package delivery, medical delivery, and agriculture [1, 2, 3, 4, 5, 6, 7, 8]. To ensure safe operation, drones need a secure and stable wireless connectivity for control and command (CC) and payload communications [9]. Conventionally, drones operate on the licensed-free industrial, scientific, and medical (ISM) radio band (2.4 GHz) which the operational range of drones is limited to the visual line-of-sight (LoS) range [10]. To unleash drones' potential, a beyond visual line-of-sight (BVLoS) connectivity is required to be established [11]. The cellular network has recently been considered one of the main enablers for developing advanced drone use cases [12]. Cellular networks can provide wide-area, quality of service (QoS), high data rate, low latency, and reliable connectivity for both terrestrial [13] and drone user equipments (UEs) [14]. In addition, utilizing the existing terrestrial cellular networks for drone connectivity can facilitate the drone ecosystem's growth, without the need to develop a new dedicated infrastructure for drone wireless communications [15]. However, using existing cellular networks to provide connectivity to the flying drone seems challenging. With an increasing height above the ground the radio environmentchanges [15], and some problems arise, such as mobility management [16] and severe interference between drone UEs and terrestrial UEs [15]. Figure 1 illustrates a scenario when a low altitude small drone flies above the terrestrial base stations (BSs). Due to the high probability of line-of-sight (LoS) link in higher altitudes, drone communications suffer from both uplink and downlink interferences [17]. Moreover, terrestrial network planning is optimized for ground UEs, and BS antennas are tilted downwards to prevent inter-cell interference and provide service for ground UEs via antennas' main lobes [18]. Meanwhile, drones that fly above the BSs are served by the antennas' sidelobes, which cause severe challenges for interference and mobility management [11]. To better understand the Long Term Evolution (LTE) network's capability to provide wireless connectivity for low altitude small drones, the 3 rd Generation Partnership Project (3 GPP) conducted research on enhanced LTE support for aerial vehicles [19]. The primary purpose of that study was to evaluate drone UEs' mobility performance, including the handover (HO) procedure and cell selection. In addition, recently theoretical research has been conducted on topics such as autonomous navigation [20], joint trajectory and communication design [21], energy efficiency and trajectory optimization [22; 23], hybrid-duplex UAV with join detection [24], 3D coverage analysis [25], and spectrum sharing [26]. Among these research topics, channel measurement and modeling have drawn academic interest because of the behavior changes of radio channels at high altitude and their importance in designing reliable communication links for the drones' safety control and operations. The works described in [14; 15; 17; 27] studied the radio environment changes with altitude and mobility performance of cellular-connected drones based on simulation results. These works investigated drone connectivity by considering parameters such as signal to interference plus noise ratio (SINR), reference signal received power (\(RSRP\)), and HO under different drone speeds and heights. The results show that by increasing the drone height the probability of LoS communications links increases, which results in higher interference in neighbor cells compared to terrestrial UEs. Moreover, results show how drones are served by sidelobes of BSs' antennas and reveal problems of handover when drones move to the BS antenna sidelobe nulls. However, these works are limited to simulation results and do not fully reflect the challenges of real-world scenarios.