etc. The article also aims to give an insight to the future scopes in the designing of UAV-assisted networks. The budding researchers will be able to identify the open research area of their interest in further development of this technology and thereby contribute to the advancement of wireless communication systems.
Keywords: Unmanned aerial vehicles, UAV, channel modeling of UAV, trajectory optimization, cellular assisted UAV, UAV mmWave communication
2.1 Introduction
On account of their high mobility and their capability of being deployed easily, on-demand UAVs have been used in a wide range of applications like in the military, telecommunication, surveillance and monitoring, rescue operations, and so on [1, 2]. They have played a vital role in numerous applications spanning over various areas of human life. UAVs have been envisioned to support various applications in 5G wireless networks [3–5]. Over the past 40 years, UAV-centric research has focused on a wide range of issues in UAV assisted wireless networks. Work is still continuing and new applications with their own challenges and solutions are being explored daily. Compared to the terrestrial communication systems, these on-demand UAV networks have to be critically designed considering the non-stationary channels, high mobility of the UAV-user equipment, and the UAV-base station, energy and altitude constraints, and the various environmental factors affecting system performance. UAV-assisted wireless communication is a promising application for the next generation networks which are looking forward to the Internet of Things (IoT) era. As we move towards a heterogeneous communication network, the complexity in designing such networks is increasing by leaps and bounds. Here, in this article, effort has been made to bring forth the state of art and the challenges posed in designing UAV-assisted networks. Some of the open research areas identified are channel modeling of A2G links considering the communication over water bodies and highy urban scenarios, effects of higher doppler shifts in A2A links of UAV-mmWaves network, better effective interference mitigation techniques to deal with UAV-BS channel in UAV-cellular network, efficient spectrum sharing schemes for increasing network throughput and spectral efficiency of UAV-mmWave communication network, trajectory optimization, on-board energy requirements of UAVs and multidimensional UAV channel modeling. Need arises to explore more areas of this cutting edge technology of next generation communication networks. As work progresses in this area, researchers will come across more challenges to deal with.
2.2 Technical Challenges
While using UAVs in the Drone-Base Station scenario, we need to consider the network performance characterization, best method of 3D deployment of drones, allocation of both wireless as well as computational resources, optimization of flight time, and planning of UAV network. Operation in Drone-UE scenario should take into consideration issues like channel modeling, handover management, low latency control, interference management and 3D localization. To use UAVs for specific applications of wireless communication networks, factors like capability of UAV, flight constraints of UAV, energy constraints of UAV, the flying altitudes of UAV must be taken into account. Since UAV communication has distinctive channel characteristics of its own, accurate channel characterization is essential for optimum performance and efficient designing. The propagation characteristics of the highly dynamic UAV channels have not yet been properly explored, in terms of the spatial and temporal variations induced in the non-stationary channels of UAV networks. Designing of a generic channel model for UAV air to ground communications (A2G), demands for simulations and measurements to be carried out comprehensively in various environments, taking into consideration the altitudes at which the UAV is flying, it’s antenna movements, shadowing caused by UAV’s body, etc. Airframe shadowing caused due to structural design and maneuvering of small rotary UAVs is yet to be explored in detail, though preliminary studies were carried out by Sun et al. in 2017. Figure 2.1 depicts the design issues faced in the UAV-assisted communication networks.
The rest of the chapter discusses in detail the above mentioned design issues encountered in deployment of UAV-assisted communication networks, the solutions proposed till date and the open research areas that need to be worked upon for optimizing the performance of the UAV systems. Designing of UAV-assisted communication networks is a great challenge in itself.
Figure 2.1 Design issues of UAV-assisted communication networks.
2.2.1 Variations in Channel Characteristics
The control signaling and data signaling in UAV communication need two types of channels—UAV-ground and UAV–UAV channel. Both types of channels exhibit several unique characteristics.
a) Air to Ground Channel Modeling Due to complexity in the operating environments, systematic measurements and modeling of UAV-ground channels needs to be carried out as in Refs. [6, 7]. Problems to be considered are link blockage due to obstacles like terrain, buildings, shadowing during aircraft maneuvering in critical operations, multipath links due to reflections, scatterings, diffractions, from different physical contours like mountains, ground surface, foliage, water bodies, desert, etc.
Compared to the characteristics of terrestrial communication channels, the A2G channel characteristics differ in terms of coverage and capacity [8–12]. This demands for optimal designing and deployment of A2G channel models for various applications like cellular-connected UAV-UE and IoT communication. We need to consider the type of UAV, the altitude at which the UAV is placed, the angle of elevation between transmitter and receiver in the A2G link, type of propagation scenario (such as the rural scenario, suburban scenario, urban scenario, high rise urban scenario), the movements of the antennas at the UAVs, shadowing caused by the body of UAV, locations of ground users, etc. A probabilistic path loss model proposed by Hourani et al. [9, 13] has been widely adopted by researchers authoring the literature as in [14–24]. Table 2.1 lists the studies carried out till date for understanding the effect of various design parameters on the operation of A2G channel in UAV systems.
Deterministic models using environmental parameters and for studying large scale fading effects in A2G channels have been proposed in [27, 28]. The effect of propagation conditions on the coverage and optimal UAV positioning have been discussed in Refs. [29–33]. Geometric based stochastic models have been proposed for evaluating the spatial-temporal characteristics in a geometric simulation environment [34–39]. Further work needs to be carried out in the area of channel modeling of A2G links taking into consideration the communication over water bodies and communication in highly urban scenarios.
Table 2.1 Parameters determining the performance of A2G channel.
| Parameter worked upon | Reference |
| Effect of environment on path loss, delay spread, fading | [25] |
| Effect of high altitude of platform | [10, 11] |
| Effect on signal strength due to path loss and shadowing on account of various propagation scenarios and high elevation angle between transmitter and receiver. | [10] |
| Effect of low altitude UAV in suburban environments | [12] |
| Effect of angle of elevation and building height in urban environment | [26] |
b)
