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Robust, Resilient Networked Communication in Challenged Environments
In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication
Analysis, characterization and optimization of the energy efficiency on softwarized mobile platforms
Mención Internacional en el título de doctorLa inminente 5ª generación de sistemas móviles (5G) está a punto de revolucionar la industria, trayendo una nueva arquitectura orientada a los nuevos mercados verticales y servicios. Debido a esto, el 5G Infrastructure Public Private Partnership (5G-PPP) ha especificado una lista de Indicadores de Rendimiento Clave (KPI) que todo sistema 5G tiene que soportar, por ejemplo incrementar por 1000 el volumen de datos, de 10 a 100 veces m´as dispositivos conectados o consumos energéticos 10 veces inferiores. Con el fin de conseguir estos requisitos, se espera expandir los despligues actuales usando mas Puntos de Acceso (PoA) incrementando así su densidad con
múltiples tecnologías inalámbricas. Esta estrategia de despliegue masivo tiene una contrapartida en la eficiencia energética, generando un conflicto con el KPI de reducir por 10 el consumo energético. En este contexto, la comunidad investigadora ha propuesto nuevos paradigmas para alcanzar los requisitos impuestos para los sistemas 5G, siendo materializados en tecnologías como Redes Definidas por Software (SDN) y Virtualización de Funciones de Red (NFV). Estos nuevos paradigmas son el primer paso hacia la softwarización de los despliegues móviles, incorporando nuevos grados de flexibilidad y reconfigurabilidad de la Red de Acceso Radio (RAN). En esta tesis, presentamos primero un análisis detallado y caracterización de las redes móviles softwarizadas. Consideramos el software como la base de la nueva generación de redes celulares y, por lo tanto, analizaremos y caracterizaremos el impacto en la eficiencia energética de estos
sistemas. La primera meta de este trabajo es caracterizar las plataformas software disponibles para Radios Definidas por Software (SDR), centrándonos en las dos soluciones principales de código abierto: OpenAirInterface (OAI) y srsLTE. Como resultado, proveemos una metodología para analizar y caracterizar el rendimiento de estas soluciones en función del uso de la CPU, rendimiento de red, compatibilidad y extensibilidad de dicho software. Una vez hemos entendido
qué rendimiento podemos esperar de este tipo de soluciones, estudiamos un prototipo SDR construido con aceleración hardware, que emplea una plataformas basada en FPGA. Este prototipo está diseñado para incluir capacidad de ser consciente de la energía, permiento al sistema ser reconfigurado para minimizar la huella energética cuando sea posible. Con el fin de validar el diseño de nuestro sistema, más tarde presentamos una plataforma para caracterizar la energía que será empleada para medir experimentalmente el consumo energético de dispositivos reales. En nuestro enfoque, realizamos dos tipos de análisis: a pequeña escala de tiempo y a gran escala de tiempo. Por lo tanto, para validar nuestro entorno de medidas, caracterizamos a través de análisis numérico los algoritmos para la Adaptación de la Tasa (RA) en IEEE 802.11, para entonces comparar
nuestros resultados teóricos con los experimentales. A continuación extendemos nuestro
análisis a la plataforma SDR acelerada por hardware previamente mencionada. Nuestros resultados experimentales muestran que nuestra sistema puede en efecto reducir la huella energética reconfigurando el despligue del sistema.
Entonces, la escala de tiempos es elevada y presentamos los esquemas para Recursos bajo Demanda (RoD) en despliegues de red ultra-densos. Esta estrategia está basada en apagar/encender
dinámicamente los elementos que forman la red con el fin de reducir el total del consumo
energético. Por lo tanto, presentamos un modelo analítico en dos sabores, un modelo exacto que predice el comportamiento del sistema con precisión pero con un alto coste computacional y uno simplificado que es más ligero en complejidad mientras que mantiene la precisión. Nuestros resultados muestran que estos esquemas pueden efectivamente mejorar la eficiencia energética de
los despliegues y mantener la Calidad de Servicio (QoS). Con el fin de probar la plausibilidad
de los esquemas RoD, presentamos un plataforma softwarizada que sigue el paradigma SDN,
OFTEN (OpenFlow framework for Traffic Engineering in mobile Network with energy awareness).
Nuestro diseño está basado en OpenFlow con funcionalidades para hacerlo consciente de
la energía. Finalmente, un prototipo real con esta plataforma es presentando, probando así la plausibilidad de los RoD en despligues reales.The upcoming 5th Generation of mobile systems (5G) is about to revolutionize the industry,
bringing a new architecture oriented to new vertical markets and services. Due to this, the 5G-PPP
has specified a list of Key Performance Indicator (KPI) that 5G systems need to support e.g. increasing
the 1000 times higher data volume, 10 to 100 times more connected devices or 10 times
lower power consumption. In order to achieve these requirements, it is expected to expand the
current deployments using more Points of Attachment (PoA) by increasing their density and by
using multiple wireless technologies. This massive deployment strategy triggers a side effect in
the energy efficiency though, generating a conflict with the “10 times lower power consumption”
KPI. In this context, the research community has proposed novel paradigms to achieve the imposed
requirements for 5G systems, being materialized in technologies such as Software Defined
Networking (SDN) and Network Function Virtualization (NFV). These new paradigms are the
first step to softwarize the mobile network deployments, enabling new degrees of flexibility and
reconfigurability of the Radio Access Network (RAN).
In this thesis, we first present a detailed analysis and characterization of softwarized mobile
networking. We consider software as a basis for the next generation of cellular networks and
hence, we analyze and characterize the impact on the energy efficiency of these systems. The
first goal of this work is to characterize the available software platforms for Software Defined
Radio (SDR), focusing on the two main open source solutions: OAI and srsLTE. As result, we
provide a methodology to analyze and characterize the performance of these solutions in terms
of CPU usage, network performance, compatibility and extensibility of the software. Once we
have understood the expected performance for such platformsc, we study an SDR prototype built
with hardware acceleration, that employs a FPGA based platform. This prototype is designed
to include energy-awareness capabilites, allowing the system to be reconfigured to minimize the
energy footprint when possible. In order to validate our system design, we later present an energy
characterization platform that we will employ to experimentally measure the energy consumption
of real devices. In our approach, we perform two kind of analysis: at short time scale and large
time scale. Thus, to validate our approach in short time scale and the energy framework, we have
characterized though numerical analysis the Rate Adaptation (RA) algorithms in IEEE 802.11,
and then compare our theoretical results to the obtained ones through experimentation. Next
we extend our analysis to the hardware accelerated SDR prototype previously mentioned. Our experimental results show that our system can indeed reduce the energy footprint reconfiguring
the system deployment.
Then, the time scale of our analysis is elevated and we present Resource-on-Demand (RoD)
schemes for ultradense network deployments. This strategy is based on dynamically switch on/off
the elements that form the network to reduce the overall energy consumption. Hence, we present
a analytic model in two flavors, an exact model that accurately predicts the system behaviour
but high computational cost and a simplified one that is lighter in complexity while keeping the
accuracy. Our results show that these schemes can effectively enhance the energy efficiency of
the deployments and mantaining the Quality of Service (QoS). In order to prove the feasibility of
RoD, we present a softwarized platform that follows the SDN paradigm, the OFTEN (Open Flow
framework for Traffic Engineering in mobile Networks with energy awareness) framework. Our
design is based on OpenFlow with energy-awareness functionalities. Finally, a real prototype of
this framework is presented, proving the feasibility of the RoD in real deployments.FP7-CROWD (2013-2015) CROWD (Connectivity management for eneRgy Optimised Wireless Dense networks).-- H2020-Flex5GWare (2015-2017) Flex5GWare (Flexible and efficient hardware/software platforms for 5G network elements and devices).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Gramaglia , Marco.- Secretario: José Nuñez.- Vocal: Fabrizio Giulian
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Integrated Satellite-terrestrial networks for IoT: LoRaWAN as a Flying Gateway
When the Internet of Things (IoT) was introduced, it causes an immense change in
human life. Recently, different IoT emerging use cases, which will involve an even higher
number of connected devices aimed at collecting and sending data with different purposes
and over different application scenarios, such as smart city, smart factory, and smart
agriculture. In some cases, the terrestrial infrastructure is not enough to guarantee the
typical performance indicators due to its design and intrinsic limitations. Coverage is
an example, where the terrestrial infrastructure is not able to cover certain areas such
as remote and rural areas. Flying technologies, such as communication satellites and
Unmanned Aerial Vehicles (UAVs), can contribute to overcome the limitations of the
terrestrial infrastructure, offering wider coverage, higher resilience and availability, and
improving user\u2019s Quality of Experience (QoE). IoT can benefit from the UAVs and satellite
integration in many ways, also beyond the coverage extension and the increase of the
available bandwidth that these objects can offer. This thesis proposes the integration
of both IoT and UAVs to guarantee the increased coverage in hard to reach and out of
coverage areas. Its core focus addresses the development of the IoT flying gateway and
data mule and testing both approaches to show their feasibility.
The first approach for the integration of IoT and UAV results in the implementing of
LoRa flying gateway with the aim of increasing the IoT communication protocols\u2019
coverage area to reach remote and rural areas. This flying gateway examines the
feasibility for extending the coverage in a remote area and transmitting the data to the IoT cloud in real-time. Moreover, it considers the presence of a satellite between the
gateway and the final destination for areas with no Internet connectivity and
communication means such as WiFi, Ethernet, 4G, or LTE. The experimental results
have shown that deploying a LoRa gateway on board a flying drone is an ideal option
for the extension of the IoT network coverage in rural and remote areas.
The second approach for the integration of the aforementioned technologies is the
deployment of IoT data mule concept for LoRa networks. The difference here is the
storage of the data on board of the gateway and not transmitting the data to the IoT
cloud in real time. The aim of this approach is to receive the data from the LoRa
sensors installed in a remote area, store them in the gateway up until this flying
gateway is connected to the Internet. The experimental results have shown the
feasibility of our flying data mule in terms of signal quality, data delivery, power
consumption and gateway status.
The third approach considers the security aspect in LoRa networks. The possible
physical attacks that can be performed on any LoRa device can be performed once its
location is revealed. Position estimation was carried out using one of the LoRa signal
features: RSSI. The values of RSSI are fed to the Trilateration localization algorithm to
estimate the device\u2019s position. Different outdoor tests were done with and without the
drone, and the results have shown that RSSI is a low cost option for position estimation
that can result in a slight error due to different environmental conditions that affect
the signal quality.
In conclusion, by adopting both IoT technology and UAV, this thesis advances the
development of flying LoRa gateway and LoRa data mule for the aim of increasing the
coverage of LoRa networks to reach rural and remote areas. Moreover, this research
could be considered as the first step towards the development of high quality and
performance LoRa flying gateway to be tested and used in massive LoRa IoT networks
in rural and remote areas
Internet of Things and Sensors Networks in 5G Wireless Communications
This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors
Internet of Things and Sensors Networks in 5G Wireless Communications
The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic
Coexistence and interference mitigation for WPANs and WLANs from traditional approaches to deep learning: a review
More and more devices, such as Bluetooth and IEEE 802.15.4 devices forming Wireless Personal Area Networks (WPANs) and IEEE 802.11 devices constituting Wireless Local Area Networks (WLANs), share the 2.4 GHz Industrial, Scientific and Medical (ISM) band in the realm of the Internet of Things (IoT) and Smart Cities. However, the coexistence of these devices could pose a real challenge—co-channel interference that would severely compromise network performances. Although the coexistence issues has been partially discussed elsewhere in some articles, there is no single review that fully summarises and compares recent research outcomes and challenges of IEEE 802.15.4 networks, Bluetooth and WLANs together. In this work, we revisit and provide a comprehensive review on the coexistence and interference mitigation for those three types of networks. We summarize the strengths and weaknesses of the current methodologies, analysis and simulation models in terms of numerous important metrics such as the packet reception ratio, latency, scalability and energy efficiency. We discover that although Bluetooth and IEEE 802.15.4 networks are both WPANs, they show quite different performances in the presence of WLANs. IEEE 802.15.4 networks are adversely impacted by WLANs, whereas WLANs are interfered by Bluetooth. When IEEE 802.15.4 networks and Bluetooth co-locate, they are unlikely to harm each other. Finally, we also discuss the future research trends and challenges especially Deep-Learning and Reinforcement-Learning-based approaches to detecting and mitigating the co-channel interference caused by WPANs and WLANs
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