Underlay Drone Cell for Temporary Events: Impact of Drone Height and Aerial Channel Environments

Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-line-of-sight (NLOS) links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the non-trivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.Comment: This work is accepted to appear in IEEE Internet of Things Journal Special Issue on UAV over IoT. Copyright may be transferred without notice, after which this version may no longer be accessible. arXiv admin note: text overlap with arXiv:1801.0594

Drone-Assisted Wireless Communications

In order to address the increased demand for any-time/any-where wireless connectivity, both academic and industrial researchers are actively engaged in the design of the fifth generation (5G) wireless communication networks. In contrast to the traditional bottom-up or horizontal design approaches, 5G wireless networks are being co-created with various stakeholders to address connectivity requirements across various verticals (i.e., employing a top-to-bottom approach). From a communication networks perspective, this requires obliviousness under various failures. In the context of cellular networks, base station (BS) failures can be caused either due to a natural or synthetic phenomenon. Natural phenomena such as earthquake or flooding can result in either destruction of communication hardware or disruption of energy supply to BSs. In such cases, there is a dire need for a mechanism through which capacity short-fall can be met in a rapid manner. Drone empowered small cellular networks, or so-called \quotes{flying cellular networks}, present an attractive solution as they can be swiftly deployed for provisioning public safety (PS) networks. While drone empowered self-organising networks (SONs) and drone small cell networks (DSCNs) have received some attention in the recent past, the design space of such networks has not been extensively traversed. So, the purpose of this thesis is to study the optimal deployment of drone empowered networks in different scenarios and for different applications (i.e., in cellular post-disaster scenarios and briefly in assisting backscatter internet of things (IoT)). To this end, we borrow the well-known tools from stochastic geometry to study the performance of multiple network deployments, as stochastic geometry provides a very powerful theoretical framework that accommodates network scalability and different spatial distributions. We will then investigate the design space of flying wireless networks and we will also explore the co-existence properties of an overlaid DSCN with the operational part of the existing networks. We define and study the design parameters such as optimal altitude and number of drone BSs, etc., as a function of destroyed BSs, propagation conditions, etc. Next, due to capacity and back-hauling limitations on drone small cells (DSCs), we assume that each coverage hole requires a multitude of DSCs to meet the shortfall coverage at a desired quality-of-service (QoS). Hence, we consider the clustered deployment of DSCs around the site of the destroyed BS. Accordingly, joint consideration of partially operating BSs and deployed DSCs yields a unique topology for such PS networks. Hence, we propose a clustering mechanism that extends the traditional Mat\'{e}rn and Thomas cluster processes to a more general case where cluster size is dependent upon the size of the coverage hole. As a result, it is demonstrated that by intelligently selecting operational network parameters such as drone altitude, density, number, transmit power and the spatial distribution of the deployment, ground user coverage can be significantly enhanced. As another contribution of this thesis, we also present a detailed analysis of the coverage and spectral efficiency of a downlink cellular network. Rather than relying on the first-order statistics of received signal-to-interference-ratio (SIR) such as coverage probability, we focus on characterizing its meta-distribution. As a result, our new design framework reveals that the traditional results which advocate lowering of BS heights or even optimal selection of BS height do not yield consistent service experience across users. Finally, for drone-assisted IoT sensor networks, we develop a comprehensive framework to characterize the performance of a drone-assisted backscatter communication-based IoT sensor network. A statistical framework is developed to quantify the coverage probability that explicitly accommodates a dyadic backscatter channel which experiences deeper fades than that of the one-way Rayleigh channel. We practically implement the proposed system using software defined radio (SDR) and a custom-designed sensor node (SN) tag. The measurements of parameters such as noise figure, tag reflection coefficient etc., are used to parametrize the developed framework

Integrating Drones and Wireless Power Transfer into Beyond 5G Networks

As fifth generation (5G) standards have been established and 5G commercial products are just around the corner, both academia and industry have started to look at requirements for beyond 5G networks. Network flexibility and long battery life are among the key requirements for beyond 5G wireless communication systems. These critical requirements, which have not been sufficiently addressed in the previous generations, are the focus of this thesis. The first half of this thesis explores two important use cases of drones to provide flexible communication networks. First, the performance of a cellular network with underlay drone cell for temporary events inside a stadium is studied. Using stochastic geometry, a general analytical framework is proposed to analyze the uplink and the downlink coverage probabilities for both the aerial and the terrestrial systems. Our results show that for urban environment and dense urban environment, the drone is best deployed at a low height (e.g., 200 m or lower), regardless of the distance between the center of the stadium and the terrestrial base station. However, for suburban environment and high-rise urban environment, the best drone altitude varies. Second, the performance of emergency information dissemination in public safety scenarios using drone is studied. A drone-assisted multihop multicast device-to-device (D2D) network is considered, where an emergency alert message broadcasted by a drone at the first time slot is multicasted by the D2D users that have successfully received the message through multihop. The impact of different system parameters on the link and the network performance is investigated. Our results demonstrate that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. Under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m. The second half of this thesis investigates wireless power transfer networks. Specifically, the use of power beacons in a millimeter wave wireless ad hoc network is considered, where transmitters adopt the harvest-then-transmit protocol. First, the characteristic of the aggregate received power from power beacons is analyzed and the lognormal distribution is found to provide the best complementary cumulative distribution function approximation compared to other distributions considered in the literature. Then, a tractable model with discrete transmit power for each transmitter is proposed to compute the channel coverage probability and the total coverage probability. Our results show that our model provides a good accuracy and reveal the impact of different system parameters on the total coverage probability. Our results also illustrate that under practical setups, for power beacon transmit power of 50 dBm and transmitters with maximum transmit power between 20 - 40 dBm, which are safe for human exposure, the total coverage probability is around 90%. Thus, it is feasible and safe to power transmitters in a millimeter wave ad hoc network using power beacons

Unmanned aerial vehicles (UAVs) for wireless communication and networks : potentials and design challenges

Unmanned aerial vehicles (UAVs) are mostly considered by the military for surveillance and reconnaissance operations, and by hobbyists for aerial photography. However, in recent years, the UAV operations have been extended for civilian and commercial purposes due to their agile and cost-effective deployment. UAVs appear to be more prolific platforms to enable wireless communication due to their better line-of-sight (LOS) channel conditions as compared with the fixed base stations (BSs) in terrestrial communication which suffer from severe path loss, shadowing, and multipath fading in more challenging propagation environments. In UAV-enabled wireless communications, the UAV can either act as a complementary aerial BS to provide on-demand communication or as an aerial user equipment (UE) which is operated by the existing cellular network. Several challenges exist in the design of UAV communications which include but not limited to channel modeling, optimal deployment, interference generation, performance analysis, limited on-board battery lifetime, trajectory optimization, and unavailability of regulations and standards which are specific for UAV communication and networking. This thesis particularly investigates some important design challenges for safe and reliable functionalities of UAV for wireless communication and networking. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non-stationary channels. Therefore, first and foremost, this thesis provides an extensive review of the measurement methods proposed for UAV channel modeling and discusses channel modeling efforts for air-to-ground and air-to-air channels. Furthermore, knowledge-gaps are identified to realize accurate UAV channel models. The efficient deployment strategy is imperative to compensate the adverse impact of interference on the coverage area performance of multiple UAVs. As a result, this thesis proposes an optimal deployment strategy for multiple UAVs in presence of downlink co-channel interference in the worst-case scenario. In particular, this work presents coordinated multi-UAV strategy in two schemes. In the first scheme, symmetric placement of UAVs is assumed at a common optimal altitude and transmit power. In the second scheme, asymmetric deployment of UAVs with different altitudes and transmit powers is assumed. The impact of various system parameters, such as signal-to interference-plus-noise ratio (SINR) threshold, separation distance between UAVs, and the number of UAVs and their formations are carefully studied to achieve the maximum coverage area inside and to reduce the unnecessary coverage expansion outside the target area. Fundamental analysis is required to obtain the optimal trade-off between the design parameters and performance metrics of any communication systems. This thesis particularly considers two emerging scenarios for evaluating performance of UAV communication systems. In the first scenario, the uplink UAV communication system is considered where the ground user follows the random waypoint (RWP) model for user mobility, the small-scale channel fading follows the Nakagami-m model, and the uplink interference is modeled by Gamma approximation. Specifically, the closed-form expressions for the probability density function (PDF), the cumulative distribution function (CDF), the outage probability, and the average bit error rate (BER) of the considered UAV system are derived as performance metrics. In the second scenario, the downlink hybrid caching system is considered where UAVs and ground small-cell BSs (SBSs) are distributed according to two independent homogeneous Poisson point processes (PPPs), and downlink interference is modeled by the Laplace transforms. Specifically, the analytical expressions of the successful content delivery probability and energy efficiency of the considered network are derived as performance metrics. In both scenarios, results are presented to demonstrate the interplay between the communication performance and the design parameters