# Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage
## 2 Background  
The design challenge that a Drone-Assisted Radio Access Network (DA-RAN) aims to achieve is to optimize multiple DC flying altitudes and also have maximum radio coverage in a specified area while keeping within the constraint boundaries. The advantages of DA-RANs are that each BS can deploy multiple DCs to operate within a specified DA or CH such as a crowded stadium, traffic-congested area, areas suffering from communication loss due to any natural or artificial disaster, etc. They can also act as edge servers to connect more DCs in a mesh network outside the typical range of a BS. CHs created by special events such as concerts or sporting events, etc., are dynamically changing in spatial and temporal domains; hence, DCs need to be deployed or redeployed accordingly. Three-Dimensional (3D) DC deployment problems have been an area of extensive research and multiple experiments have been conducted where DCs are deployed to act as an extension of a BS or as edge servers and improve signal strength [22]. [PERSON], [PERSON] et al. introduced a multi-tier-drone cell deployment complementing the terrestrial Heterogeneous Networks (HetNets) [23]; challenges regarding multi-tier drone networks are also discussed and addressed in the paper. Finally, a Drone-cell Management Framework (DMF) was proposed and the benefits of the proposed solution and its benefits in future RANs is demonstrated via a case study. [PERSON], [PERSON] et al. proposed a polynomial-time algorithm with successive DC placement to minimize the number of UAV Mobile Base Stations (MBs) or DCs needed to maximize the radio coverage for a group of Ground Terminals (GTs) [25]. In this scenario, macro BSs are placed one after the other starting along the perimeter and then in a spiral pattern towards the center for any uncovered GT until all the GTs are covered by the DC [25]. A Spectrum Sharing network of DCs was researched by [PERSON], [PERSON] et al. [26], where a 3D Poisson Point process is used to find the optimal density of DCs to maximize the network throughput while satisfying the cellular network efficiency constraint. One of the key research studies was the creation of a dedicated communication model for an Air-to-Ground (A2G) wireless link. The DC placement is a 3D problem, and hence, the terrestrial RAN communication channels are not suitable for communication between hovering UAVs and terrestrial devices. [PERSON] in his paper proposed an Air-to-Ground communication model that takes into consideration the Line of Sight (LoS) and non-Line of Sight (nLoS) probability links in different urban scenarios [27]. It has been mainly used to focus on a single performance metric and optimal deployment positions. [PERSON], [PERSON] et al. used a constrained K-means clustering approach to minimize the total transmitting power of DCs for optimal trajectory and deployment while enabling a reliable uplink of information from ground Internet-of-Things (IoT) devices [28]. Based on simulations and testing, the approach reduced the total transmit power of the IoT devices by 45% when compared to a static DC. Similarly, another optimal DC placement algorithm was developed by [PERSON], [PERSON] et al. to maximize the number of covered users with minimum power consumption. [PERSON], [PERSON] et al. proposed the solution by decoupling the Unmanned Aerial Vehicle Mounted Base Stations (UAV-BSs) into vertical and horizontal dimensions, simplifying the placement problem and then solving it [29]. [PERSON], [PERSON] et al. also adopted the 3D Poisson Point process to optimize the density of DCs and also maximize the DC network throughput while satisfying the cellular network efficiency constraints [26]. The downlink coverage probability for the Rayleigh fading channel was derived in terms of an explicit equation by [PERSON], [PERSON] et al., and the optimal height, coverage probability and density of DCs were studied [30]. Taking into account the user mobility, [PERSON], [PERSON] et al.