###### Abstract  
The unmanned aerial vehicle (UAV) industry is moving toward beyond visual line of sight (BVLOS) operations to unlock future internet of drones applications, including unmanned environmental monitoring and long-range delivery services. A reliable and ubiquitous mobile communication link plays a vital role in ensuring flight safety. Cellular networks are considered one of the main enablers of BVLOS operations. However, the existing cellular networks are designed and optimized for terrestrial use cases. To investigate the reliability of provided aerial coverage by the terrestrial cellular base stations (BSs), this article proposes six machine learning-based models to predict reference signal received power (RSRP) and reference signal received quality (RSRQ) based on the multiple linear regression, polynomial, and logarithmic methods. In this regard, first, a UAV-to-BS measurement campaign was conducted in a 4G LTE network within a suburban environment. Then, the aerial coverage was statistically analyzed and the prediction methods were developed as a function of distance and elevation angle. The results reveal the capability of terrestrial BSs in providing aerial coverage under some circumstances, which mainly depends on the distance between the UAV and BS and flight height. The performance evaluation shows that the proposed RSRP and RSRQ models achieved RMSE of 4.37 dBm and 2.71 dB for testing samples, respectively. A Article Reliable Aerial Mobile Communications with RSRP & RSRQ Prediction Models for the Internet of Drones: A Machine Learning Approach  
22222552222255222225552222225 Conventionally, most drones operate on the license-free industrial, scientific, and medical (ISM) radio band (2.4 GHz) as a direct link. Although establishing this link is low cost and simple, it suffers from low range, low data rate, and vulnerability to interference. Hence it is not suitable for BVLOS applications. Although satellite links can provide glob-al coverage, their equipment is costly, heavy, and energy-consuming. In addition, a satellite link suffers from high latency and large signal attenuation, where these features make satellite communication unsuitable for most drone use cases. An ad hoc network, on the other hand, is considered a robust and adaptable wireless technology. Nevertheless, it suffers from technical issues such as low spectrum efficiency, intermitted connectivity, and complex routing protocols [8]. Among the existing wireless technologies, the cellular network has recently been considered one of the main enablers for large-scale UAV communications [9]. In addition, the terrestrial cellular networks already exist; hence, there is no need to develop a new dedicated infrastructure for UAV wireless communications. The main question is whether a cellular network can provide a reliable communication link to ensure that UAVs can fly BVLOS safely. In general, the existing 4G and 5G cellular networks provide ubiquitous coverage with low latency and a high-speed data rate for terrestrial users [10], whereas, at the altitudes below base stations' (BSs) heights, the existing cellular networks can meet the CC and payload communication requirements to provide safe mobile connectivity for UAVs [11]. However, existing cellular networks are designed for terrestrial users and providing connectivity to the flying drone is challenging. On the one hand, with increasing height above the ground, the radio environment changes, and some problems arise, such as handover (HO) and mobility management [12] and severe interference between aerial users (UAVs) and terrestrial users [13]. On the other hand, the transmitting antennas are tilted down; therefore, there is a severe reduction in the antenna gain at higher altitudes, leading to lower link reliability and data rate [14]. Figure 1 illustrates a scenario when a low-altitude UAV flies over the terrestrial BSs. By enhancing the flight height, the probability of line-of-sight (LoS) communications in-creases.