Drone Empowered Small Cellular Disaster Recovery Networks for Resilient Smart Cities

Resilient communication networks, which can continue operations even after a calamity, will be a central feature of future smart cities. Recent proliferation of drones propelled by the availability of cheap commodity hardware presents a new avenue for provisioning such networks. In particular, with the advent of Google’s Sky Bender and Facebook’s internet drone, drone empowered small cellular networks (DSCNs) are no longer fantasy. DSCNs are attractive solution for public safety networks because of swift deployment capability and intrinsic network reconfigurability. While DSCNs have received some attention in the recent past, the design space of such networks has not been extensively traversed. In particular, co-existence of such networks with an operational ground cellular network in a post-disaster situation has not been investigated. Moreover, design parameters such as optimal altitude and number of drone base stations, etc., as a function of destroyed base stations, propagation conditions, etc., have not been explored. In order to address these design issues, we present a comprehensive statistical framework which is developed from stochastic geometric perspective. We then employ the developed framework to investigate the impact of several parametric variations on the performance of the DSCNs. Without loss of any generality, in this article, the performance metric employed is coverage probability of a down-link mobile user. It is demonstrated that by intelligently selecting the number of drones and their corresponding altitudes, ground users coverage can be significantly enhanced. This is attained without incurring significant performance penalty to the mobile users which continue to be served from operating ground infrastructure

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

Performance Analysis of UAV Enabled Disaster Recovery Network: A Stochastic Geometric Framework based on Matern Cluster Processes

Drones will be employed by Facebook and Google for capacity off-loading in front/back hauling scenarios utilizing drone-empowered autonomous heterogeneous networks. But in another application, drone-based, post-disaster recovery of communication networks will also be of crucial importance in the design of future smart cities. So, in order to address the design issues of these latter networks, we present (from a stochastic geometric perspective) a comprehensive statistical framework for the spatial distribution of these hybrid user-centric drone/micro cellular networks. We introduce the novel idea of using a Stenien’s cell (with variable radius) to model the region over which the drones will be distributed and the drones will effectively form a Matern cluster process (MCP) across the original network space. We then employ this newly developed framework to investigate the impact of changing several parameters on the performance of the new drone small-cell clustered networks (DSCCNs) and we develop appropriate closed-form expressions that model the performance (later validated via Monte Carlo simulations)

Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges

Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements in sensor capabilities and computational abilities, allowing for efficient autonomous navigation and visual tracking applications. However, the demand for computationally complex tasks has increased faster than advances in battery technology. This opens up possibilities for improvements using edge computing. In edge computing, edge servers can achieve lower latency responses compared to traditional cloud servers through strategic geographic deployments. Furthermore, these servers can maintain superior computational performance compared to UAVs, as they are not limited by battery constraints. Combining these technologies by aiding UAVs with edge servers, research finds measurable improvements in task completion speed, energy efficiency, and reliability across multiple applications and industries. This systematic literature review aims to analyze the current state of research and collect, select, and extract the key areas where UAV activities can be supported and improved through edge computing

Performance Analysis of UAV Enabled Disaster Recovery Networks: A Stochastic Geometric Framework Based on Cluster Processes

In this paper, we develop a comprehensive statistical framework to characterize and model large-scale unmanned aerial vehicle-enabled post-disaster recovery cellular networks. In the case of natural or man-made disasters, the cellular network is vulnerable to destruction resulting in coverage voids or coverage holes. Drone-based small cellular networks (DSCNs) can be rapidly deployed to fill such coverage voids. Due to capacity and back-hauling limitations on drone small cells (DSCs), each coverage hole requires a multitude of DSCs to meet the shortfall coverage at a desired quality-of-service. Moreover, ground users also tend to cluster in hot-spots in a post-disaster scenario. Motivated by this fact, we consider the clustered deployment of DSCs around the site of a destroyed BS. Joint consideration partially operating BSs and deployed DSCs yields a unique topology for such public safety networks. Borrowing tools from stochastic geometry, we develop a statistical framework to quantify the down-link performance of a DSCN. Our proposed clustering mechanism extends the traditional Matern and Thomas cluster processes to a more general case, where cluster size is dependent upon the size of the coverage hole. We then employ the newly developed framework to find closed-form expressions (later verified by Monte-Carlo simulations) to quantify the coverage probability, area spectral efficiency, and the energy efficiency for the down-link mobile user. Finally, we explore several design parameters (for both of the adopted cluster processes) that address optimal deployment of the network (i.e., number of drones per cluster, drone altitudes, and transmit power ratio between the traditional surviving base stations and the drone base stations)

Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios

Radiocommunication networks are one of the main support tools of agencies that carry out actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these communications technologies from narrowband to broadband and integrated to information technologies to have an effective action before society. Understanding that this problem includes, besides the technical aspects, issues related to the social context to which these systems are inserted, this study aims to construct scenarios, using several sources of information, that helps the managers of the PPDR agencies in the technological decisionmaking process of the Digital Transformation of Mission-Critical Communication considering Smart City scenarios, guided by the methods and approaches of Technological Assessment (TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários, utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de Avaliação Tecnológica (TA)

Leveraging Technology and Innovation for Disaster Risk Management and Financing

The Asia-Pacific Economic Cooperation (APEC) region is highly exposed to disaster and climate risks, accounting for more than 80% of global economic losses from disaster events in the last 20 years. The destruction and disruption that usually follow disaster events pose an important challenge to economic development and can perpetuate vulnerability. Despite substantial investment in reducing risk across the region, economic losses from disaster events continue to increase at a much faster rate than gross domestic product, implying that the relative economic burden is increasing over time. Efforts to enhance the reach of insurance and other financial protection tools have not significantly reduced the share of economic losses borne by households, businesses, and governments, which often lack the capacity to absorb these impacts. A changing climate as well as continued population growth and asset accumulation in areas exposed to disaster and climate risks is expected to exacerbate these challenges—with particular implications for vulnerable groups with limited economic resources. Enhancing resilience in the face of increasing natural hazards, exposure, and vulnerability will require investments in reducing the economic, social, and financial impacts of disasters by improving risk and impact assessment and leveraging those improvements to invest in risk reduction, preparedness, and response. APEC finance ministers have long recognized the need to build financial resilience to disaster risks and have included this objective in their work for a number of years. The Cebu Action Plan, approved by APEC finance ministers in 2015, aims to enhance financial resilience against economic shocks, including by “developing innovative disaster risk financing and insurance mechanisms (including micro insurance) to enable APEC economies exposed to natural hazards to increase their financial response to disasters and reduce their fiscal burden” (APEC 2015). Referenced by APEC finance ministers in their 2019 Joint Ministerial Statement, this report aims to contribute to this objective by supporting efforts to reduce underlying risk and develop tools to manage the financial consequences