## 1 Introduction  
It was a truism that the number of subscriptions to mobile communication networks and the amount of data consumed per user were increasing over the years, and that the newer generations were becoming more dominant than the legacy after a few years of their first deployment [1]. In the fifth generation of mobile communications (5G), on the other hand, such increase is more highlighted due to the fact that there are more demanding emerging applications, including tactile internet, 4K video streaming, online gaming, etc., and the concept of Internet of Things (IoT) was seriously proliferating and pervading our daily lives with a large inclusion in various domains, such as healthcare, manufacturing, etc. [2]. There were various concepts and technologies proposed in the literature to address the aforementioned capacity issues. The use of millimeter-wave (mmWave) frequencies, massive multi-input multioutput (mMIMO), and network densification are some of the most popular and practical ones among others [3, 4, 5, 6]. Each of these technologies has a different set of advantages and disadvantages, however, they mainly target capacity enhancement in mobile communication networks. With mmWave communications, for example, an additional spectrum added to 5G networks--it was already included in 5 GNew Radio (NR) as frequency range-2 [7]--, and thus the capacity is increased with this additional bandwidth. The use of higher carrier frequencies also enable smaller antenna sizes, which subsequently enables mMIMO antenna arrays, enhancing the capacity further [3; 5]. Network densification, on the other hand, offers deployments of smaller base stations (BSs) with comparatively less antenna transmit power to reuse the frequency band, leading to a great deal of capacity enhancement [3]. Even though all these solutions are quite beneficial in enhancing the capacity of mobile communication networks, there is still room for improvements, since the spatio-temporal changes in wireless networks pose another type of challenges. More specifically, unusual circumstances, including expositions, sport competitions, and musical concerts, where much more people than normal gather together and significantly increase the demand for wireless communications are required to be tackled in a more sophisticated and intelligent manner. This is mainly because such kind of events do not happen pretty often (only few times a year); hence, it is not a good idea to design the network by taking them into consideration. In this regard, BS mounted on UAVs (which will be referred as to UAV BS hereafter) was a promising solution to meet the strict user requirements of coverage, capacity, and quality of service (QoS). With the dawn of 5G network and related technologies, the user requirements are getting diverse as the users are from a diverse groups including conventional user equipments (UEs), IoT devices, machines, vehicles, etc. The UAV-assisted communication system is a solid use-case for the next generation of mobile communications given that UAVs are flexible, easy-to-deploy, and cost-efficient [8]. This provides a boost to the terrestrial cellular infrastructure as UAVs can be deployed to provide the extra coverage, or increase the capacity in the given area. The primary research challenges regarding the UAV-assisted communication systems are as follows: (i) determining optimal positions of the UAVs; (ii) finding optimal UAV trajectory; and (iii) meeting the regional regulations for UAVs. Energy efficient networking with UAV BSs is at the core of the discussion, since the UAVs are battery operated and have limited energy capacity.