A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks

The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Seeing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. Then, this paper presents an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.Comment: Submitted to IEEE GLOBECOM 2017, 7 pages and 4 figure

Architecture of a cognitive non-line-of-sight backhaul for 5G outdoor urban small cells

Densely deployed small cell networks will address the growing demand for broadband mobile connectivity, by increasing access network capacity and coverage. However, most potential small cell base station (SCBS) locations do not have existing telecommunication infrastructure. Providing backhaul connectivity to core networks is therefore a challenge. Millimeter wave (mmW) technologies operated at 30-90GHz are currently being considered to provide low-cost, flexible, high-capacity and reliable backhaul solutions using existing roof-mounted backhaul aggregation sites. Using intelligent mmW radio devices and massive multiple-input multiple-output (MIMO), for enabling point-to-multipoint (PtMP) operation, is considered in this research. The core aim of this research is to develop an architecture of an intelligent non-line-sight (NLOS) small cell backhaul (SCB) system based on mmW and massive MIMO technologies, and supporting intelligent algorithms to facilitate reliable NLOS street-to-rooftop NLOS SCB connectivity. In the proposed architecture, diffraction points are used as signal anchor points between backhaul radio devices. In the new architecture the integration of these technologies is considered. This involves the design of efficient artificial intelligence algorithms to enable backhaul radio devices to autonomously select suitable NLOS propagation paths, find an optimal number of links that meet the backhaul performance requirements and determine an optimal number of diffractions points capable of covering predetermined SCB locations. Throughout the thesis, a number of algorithms are developed and simulated using the MATLAB application. This thesis mainly investigates three key issues: First, a novel intelligent NLOS SCB architecture, termed the cognitive NLOS SCB (CNSCB) system is proposed to enable street-to-rooftop NLOS connectivity using predetermined diffraction points located on roof edges. Second, an algorithm to enable the autonomous creation of multiple-paths, evaluate the performance of each link and determine an optimal number of possible paths per backhaul link is developed. Third, an algorithm to determine the optimal number of diffraction points that can cover an identified SCBS location is also developed. Also, another investigated issue related to the operation of the proposed architecture is its energy efficiency, and its performance is compared to that of a point-to-point (PtP) architecture. The proposed solutions were examined using analytical models, simulations and experimental work to determine the strength of the street-to-rooftop backhaul links and their ability to meet current and future SCB requirements. The results obtained showed that reliable multiple NLOS links can be achieved using device intelligence to guide radio signals along the propagation path. Furthermore, the PtMP architecture is found to be more energy efficient than the PtP architecture. The proposed architecture and algorithms offer a novel backhaul solution for outdoor urban small cells. Finally, this research shows that traditional techniques of addressing the demand for connectivity, which consisted of improving or evolving existing solutions, may nolonger be applicable in emerging communication technologies. There is therefore need to consider new ways of solving the emerging challenges

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity