###### Abstract
With the development of sophisticated technologies, an unmanned aerial vehicle (UAV) has been advanced in recent years, achieving light weight, high flexibility and longer battery life [4]. Such advances make UAVs be utilized in a wide range of applications such as military, public safety and civil applications [5; 6; 7; 8; 9; 10]. Moreover, much attention has been paid to utilizing UAVs in 5G and beyond networks to enhance the capacity due to its swift deployment, low maintenance costs and high mobility [11]. In addition, since deploying UAV into wireless communication networks does not require a cell reorganization, UAVs can provide a viable solution for the purpose into existing networks. However, UAV wireless networks still leave many issues to be resolved for stable and reliable services [12]. Unlike other wireless networks such as Mobile Ad hoc Networks (MANETs) and Vehicular Ad hoc Networks (VANETs), the rapid changes in the network topology, including the number of nodes and links in operation and the relative positions of nodes, require special attention. The routing protocol cannot be implemented by simple proactive or reactive manner because the UAV wireless network needs to be reorganized repeatedly when a UAV is out of service. Furthermore, an instantaneous management of users' links transferring from an inactive UAV to an active UAV is challenging [13]. Lastly, UAV wireless networks require energy efficiency to prolong the lifetime of networks [12]. Most of the issues are related to the configuration of UAV wireless networks because it determines a communications link condition, an optimal routing protocol and an efficient energy management of networks. In other words, the performance of UAV wireless networks depends on the position of UAVs, which changes the channel conditions between ground node and UAV or between UAVs. Therefore, optimal UAV deployment can maximize the service coverage, the overall throughput and the lifetime of networks when UAVs are deployed as aerial base or relay stations in wireless communication networks. In addition, the data collection from massive sensors through IoT and M2M communications is crucial to realize upcoming vertical applications such as smart factory, smart farm and smart city. To this end, UAVs are being used as the UAV aggregator in wireless sensor networks to collect data from and disseminate information to sensors. However, the energy efficiency and mission complete time are major issues in wireless sensor networks to prolong the network lifetime and to save the power at both sensors and UAV, hence the studieson UAV trajectory, along which UAV flies have been paid attention to minimize energy consumption in wireless sensor networks. There have been extensive studies on optimal UAV deployment and trajectory to extend cell coverage, improve throughput, reduce energy consumption, and ensure reliable connectivity of UAV wireless networks. These can provide the desired solutions on not only 5G, but beyond 5G networks to extend the service coverage, thereby enhancing the overall capacity. In this paper, we provide extensive survey on research conducted for UAV deployment and trajectory to enhance the capacity of UAV wireless networks and to manage them efficiently, so as to encourage further studies on UAV wireless networks. Current challenges and future research directions are summarized at the end of this paper. Our paper is organized as follows. Section 2 addresses use cases, practical applications and characteristics of UAV wireless networks. In Section 3, we present the studies on UAV deployment and trajectory to extend the coverage and improve the performance of UAV wireless networks, and Section 4 summarizes the lessons learned from the survey. Section 5 provides open problems and future research issues on UAV wireless networks, and Section 6 concludes the paper.