# Resource Allocation of Multiple Base Stations for Throughput Enhancement in UAV Relay Networks
## 1 Introduction  
With the rapid advances in unmanned aerial vehicle (UAV) technologies, UAVs have been utilized in a wide range of applications, such as military, public safety, and civil applications [1; 2; 3; 4; 5; 6; 7]. Specifically, considerable attention has been paid to enhancing the network capacity, utilizing the UAV as an aerial node, which forms the UAV network. The UAV base station (BS) is considered a key technology to satisfy the service requirement of the fifth generation (5G) and beyond networks [8; 9; 10; 11]. The UAV relay node, which forms the UAV relay network (URN), can provide an extra communication link to the remote user equipment (UE) [12; 13]. The demand for UAV networks is growing, hence, the research studies have improved the performances of UAV networks. UAV networks possess unique features, such as high aerial node mobility, dynamic topology, intermittent links, and power constraints [1]. These features are quite different from those in mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs); therefore, protocols for UAV networks need to be developed, considering the unique features of UAV networks. Even though UAV networks have different features from MANETs and VANETs, they have been applied to support them. Ref. [14] examined the integration of UAV networks with vehicle networks in VANETs to aid in the routing process and the detection of malicious vehicles. The proposed routing protocol achieves gains of 16% and 7% in packet delivery ratio and malicious vehicle detection, respectively,cooperating with UAV networks. In addition, UAV networks can play an important role in realizing safer autonomous vehicles by sharing traffic or accident information quickly with vehicles within a monitoring range [15; 16]. Another unique feature of UAV networks is the strong air-to-ground and air-to-air line-of-sight(LOS) channel link. Ref. [17] provided a comprehensive survey of the design of UAV channel characteristics with field measurements and a statistical channel model. Empirical, deterministic, stochastic, and geometry-based stochastic modeling approaches are summarized with their pros and cons. The deployment and trajectory of UAVs have emerged as significant research areas in the construction of UAV networks since they determine the channel conditions between a ground node and a UAV or between UAVs. Ref. [13] summarized research studies on UAV deployment and trajectory when a UAV served as an aerial BS, a relay station (RS), or an aggregator. The deployment of UAV BS and RS aims to maximize the coverage area, overall throughput, and spectral efficiency, and minimize the transmit delay and power. When the UAV is applied as an aggregator to collect data from or to disseminate information to devices or sensors, minimizing energy consumption and mission completion time is crucial to extending the network lifetime due to the power constraints on the UAV. Machine learning (ML) frameworks are integrated into UAV deployment and trajectory to satisfy the target performances of applications. In [18], the authors proposed the echo state network (ESN)-based prediction algorithm and multi-agent Q-learning-based placement algorithm for the joint optimization of UAV deployment and power control. The authors in [19] introduced Q-learning to maximize the sum rate, and the proposed algorithm can learn the network topology for unknown environments to improve the performance of the network. Due to the inherent nature of wireless communications, UAV networks are prone to security threats. Ref. [20] provided a systematic survey for secure communication in IoT-based UAV networks. IoT-based UAV networks consist of interconnected UAVs, which are equipped with sensors. Physical and logical attacks are defined, and solutions based on encryption, blockchain, and software-defined networking (SDN) are summarized. The physical attacks, and the threats that degrade the quality-of-service (QoS) in UAV networks or disable reliable transmission, are of considerable concern. Ref.