# Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey
## 5 Radio Surveillance by UAV-BSs  
The deployment of unmanned aerial vehicles (UAVs) as UAV base stations (UAV-BSs) has been considered a feasible solution to surveil network users and to provide network coverage in scenarios where the conventional ground network is inaccessible or overloaded due to emergency events. Due to its mobility, fast deployment, and corporation, UAV-BSs can assist wireless communication networks in a variety of scenarios, such as serving  
Figure 7: Illustration of motion camouflage: a pursuer flies towards a moving target, camouflaging its motion by staying on the continually changing camouflage constraint lines. users in severe shadow or interference conditions. For UAV-BSs, a fundamental research problem is its optimal deployment. An increasing number of publications have investigated the optimal deployment of UAV-BSs for improving network performance [20; 101; 102; 103; 104; 105; 106; 107; 108; 109; 110; 111]. The search results from Web of Science Core Collection show that the research related to the deployment/placement of UAV-BSs has increased rapidly since 2015, as indicated in Figure 8. An example of UAV-BSs' application scenario can be seen in Figure 9. We now present a brief review of some representative work on this topic. References [101; 102; 103] investigated the problem of deploying UAV-BSs to serve mobile users based on a priori user distributions on a street graph. The authors assume that the user distributions represent traffic demand at a specific location in the city. The 3D deployment problem of UAV-BSs was formulated as a mixed-integer nonlinear problem (MINLP) in Reference [20], and the problem was solved using the interior-point optimizer of the MOSEK solver and bisection search. References [104; 105] studied the UAV-BSs' deployment problem without pre-known locations of users, in which a searching mechanism was adopted by the UAV-BSs to find the users. In addition to mobility, another major difference between a UAV-BS and a ground BS is that UAV-BSs rely on wireless connections for the backhaul links, whereas ground-BSs usually have fixed-wired backhaul links. Thus, one of the biggest challenges in the deployment of UAV-BSs is the availability of reliable wireless backhaul links. Existing literature has considered various aspects regarding UAV-BSs' deployment for wireless coverage, but the backhaul limitations of UAV-BSs have not been treated in many details. The backhaul links of UAV-BSs may be dedicated, satellite-based,  
Figure 8: Number of publications on deployment/placement of UAV-BSs From the Web of Science Core Collection. Figure 9: Example of UAV-BSs’ application scenario. or in-band. Specifically, dedicated backhaul links could be mmWave link or free-space optical communication (FSO) between the core networks and the UAV-BSs. Satellite-based backhaul links require the UAV-BS to be equipped with a satellite transceiver for establishing the backhaul connections via satellites. As for in-band backhaul links, the main technique currently used for wireless backhaul links of LTE or WiFi is based on radio-frequency (RF) microwave [109]. Since the satellite transceiver is both energy-inefficient and expensive, the UAV-BSs with in-band or dedicated backhaul links are more practical. Existing publications have investigated various aspects regarding UAV-BSs' deployment for wireless coverage. For example, the authors of [19; 27] studied the optimal deployment of UAV-BSs to achieve energy-efficient wireless coverage. The authors in [27] formulated a problem to minimize the average transmit power of a UAV-BS that serves a set of ground users with equal and non-equal transmit power to each user, respectively. Based on the decoupling method, the authors proposed an optimal UAV-BS placement algorithm when considering the equal transmit power to each user. For the non-equal transmit power case, the authors in [27] further proposed a UAV-BS placement algorithm by using the successive convex approximation (SCA) technique.