# Artificial Intelligence-Based Autonomous UAV Networks: A Survey
### Summary of Existing Surveys  
With the increase in novel technological solutions being proposed recently in the domain of autonomous UAV networks, surveys of published articles have been conducted to provide blanket coverage to many technologies addressing this research area. In this section, we discuss some relevant latest surveys conducted in this domain. UAV coverage is one of the vital research areas. Many technologies have been developed to provide better area coverage using UAV networks. A detailed survey [12] is being conducted highlighting various problems from the UAV network's coverage perspective. The authors have classified the problems into groups and considered various constraints. The survey findings highlight the need for more intensive research studies to be carried out exploring the UAV network's coverage, inter-UAV networks' coverage, and end-to-end delays and robustness. Another survey [13] conducted in 2015 addresses the unique features of the UAV networks, which may not be adopted from the ad hoc mesh networks, vehicular technology, or any other wireless networks that already exist. The UAVs are considered unique based on their dynamic nature, the existence of intermittent links, fluid topology, and energy-conservative constraints. In this survey, the authors highlight issues related to physical, data link, network, and transport layers faced by the UAV networks. Survey findings suggest the need for cross-layer solutions to address the unique needs of the UAV networks. Moreover, the authors encouraged that those solutions that are native to UAV networks should be proposed to address the dynamic and energy-critical needs of the networks. Another unique feature of the UAV networks has been surveyed by [14]. The authors discussed in detail the channel modeling requirements of the UAV networks and how this impact on network performance and design. An in-depth survey has been conducted exploring the low-altitude platforms with ground infrastructure. Low-cost and low-power solutions are explored with empirical modeling for air-to-air and air-to-ground propagation channels. The 5G millimeter wave with UAV networks was surveyed in [15]. The authors proposed a novel taxonomy to classify recent work in this area into seven categories from physical layer considerations, i.e., antenna techniques to performance assessments. The survey highlights various open research areas and considerations to make UAV networks a greater success for both industry and research communities. [PERSON] and [PERSON] have presented the findings of an intensive survey exploring various routing techniques for UAVnetworks [16]. The survey classified the routing protocols in various groups with their performance evaluations. The authors have also pointed out various open research areas, including security, performance evaluation, and link performance. Another interesting study was conducted by [PERSON] and team [17], which highlights various aspects of cellular communications over UAVs. This survey addresses various practical aspects of the transition from a traditional cellular network to a network with flying base stations and relay nodes. The study presented various challenges around standardization and regulations, equipment, and security. The authors also highlighted their lessons learned and future directions to pave a path for upcoming research in the field. While the UAV networks are getting popular for providing better coverage, industry and network researchers have also been actively developing various techniques and solutions to make these newly evolving networks as spectrum efficient as possible. A survey based on the use of a software-defined network (SDN) and network function virtualization (NFV) in UAV networks was conducted in 2020 [18]. This study highlights the interoperability issues in UAV networks and explains how SDN and NFV can be considered a natural fit to solve this issue. The study also brings attention to open research areas of future UAV networks.