# MIMO Relaying UAVs Operating in Public Safety Scenarios
## 1 Introduction  
Public safety communication services often utilize unmanned aerial vehicles (UAVs) as a suitable tool during unfortunate events such as landslides, mountain collapses, and road accidents due to the full line of sight (LoS) probability when flying above a given height as the 3 GPP Release 15 presents [1; 2]. UAVs show superiority in comparison to existing terrestrial base stations in terms of convenient deployment for covering dead zones, easy control, coverage area adaptation, and flexibility in network reconfiguration [3]. These advantages made the European Union constitute the U-Space program to legislate UAV's integration into their aircraft system. The program objective established commercial management rules for UAVs in Europe [4]. According to [PERSON] et al. [5], UAVs can contribute to enhancing user services in heterogeneous radio access networks (RANs) as a relay (Figure 1), as Wi-Fi connected to a backhaul, as a small cell and/or base station to provide coverage extension, and as storage in delay tolerant networks for late forwarding. Indeed, drones' major user contract application is as a relay because of the costly considerations and licenses for fixed relay implementations that avoid obstacles and complex topographical regions [6]. Additionally, the user outage probability can be reduced by introducing flexible relays into the system [7]. However, the EUTRA-based technology solution on the user equipment (UE)-to-network relay presented in Release-13 is insuffcient, which is not the case for fifth-generation (5G) mobile communications and future systems [2]. Relay UAVs are studied in several aspects: fixed and mobile UAV relay applications [8; 9; 10], energy-efficient trajectories, power and resource optimization [3; 11; 12; 13; 14], multihop Single and Dual Link options [15; 16; 17], and methods to define the number of drones needed to provide connectivity during life-threatening Scenarios [15; 17]. Although it is still not possible to find a solution for every problem, the aforementioned issues are interdependent and are often collectively considered designs for heterogeneous networks (HetNets). Mobile relays are potentially more adaptable to environmental dynamics in future networks due to their ability to be closer to the ground node that needs communication support and, consequently, improves overall throughput. Most of the solutions in the literature about trajectory optimization propose both successive convex approximation (SCA) and an iterative algorithm as suboptimal solutions to a non-convex problem. Usually, the trajectory specifications (i.e., initial position, speed, route, altitudes, and direction) are associated with radio resource management parameters such as bandwidth, throughput, power allocation, channel variation, outage probability, timeslots, and latency. Energy efficiency and reliability are common constraints due to UAV power source limitations in emergency circumstances. The most frequent relaying UAV algorithms are amplify and forward (AF) and decode and forward (DF). [PERSON] [15] evaluates the utilization of single-hopping and dual-multihopping cases. The author concludes that the dual-hop multi-link option is better than the multi-hop single link option when air-to-ground path loss parameters depend on UAV positions. The researcher also concludes that decode-and-forward UAVs provide better performances than amplify-and-forward UAVs. The multihopping problem is considered a nonconvex problem by [PERSON] et al. [16] and [PERSON] [17]. [PERSON] proposes an iterative algorithm to obtain a suboptimal solution that maximizes the end-to-end throughput as it is seen in the trajectory optimization problem previously. The difference, in this case, includes parameters to avoid collision and to control average/peak transmission power in the source and the UAV relays. [PERSON] discovers that device-to-device communication (D2D) can be applied to extend coverage to overcome energy limitations on UE.