Technologies and solutions for location-based services in smart cities: past, present, and future

Location-based services (LBS) in smart cities have drastically altered the way cities operate, giving a new dimension to the life of citizens. LBS rely on location of a device, where proximity estimation remains at its core. The applications of LBS range from social networking and marketing to vehicle-toeverything communications. In many of these applications, there is an increasing need and trend to learn the physical distance between nearby devices. This paper elaborates upon the current needs of proximity estimation in LBS and compares them against the available Localization and Proximity (LP) finding technologies (LP technologies in short). These technologies are compared for their accuracies and performance based on various different parameters, including latency, energy consumption, security, complexity, and throughput. Hereafter, a classification of these technologies, based on various different smart city applications, is presented. Finally, we discuss some emerging LP technologies that enable proximity estimation in LBS and present some future research areas

Position Estimation of Robotic Mobile Nodes in Wireless Testbed using GENI

We present a low complexity experimental RF-based indoor localization system based on the collection and processing of WiFi RSSI signals and processing using a RSS-based multi-lateration algorithm to determine a robotic mobile node's location. We use a real indoor wireless testbed called w-iLab.t that is deployed in Zwijnaarde, Ghent, Belgium. One of the unique attributes of this testbed is that it provides tools and interfaces using Global Environment for Network Innovations (GENI) project to easily create reproducible wireless network experiments in a controlled environment. We provide a low complexity algorithm to estimate the location of the mobile robots in the indoor environment. In addition, we provide a comparison between some of our collected measurements with their corresponding location estimation and the actual robot location. The comparison shows an accuracy between 0.65 and 5 meters.Comment: (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

A Preliminary Study of Machine-Learning-Based Ranging with LTE Channel Impulse Response in Multipath Environment

Alternative navigation technology to global navigation satellite systems (GNSSs) is required for unmanned ground vehicles (UGVs) in multipath environments (such as urban areas). In urban areas, long-term evolution (LTE) signals can be received ubiquitously at high power without any additional infrastructure. We present a machine learning approach to estimate the range between the LTE base station and UGV based on the LTE channel impulse response (CIR). The CIR, which includes information of signal attenuation from the channel, was extracted from the LTE physical layer using a software-defined radio (SDR). We designed a convolutional neural network (CNN) that estimates ranges with the CIR as input. The proposed method demonstrated better ranging performance than a received signal strength indicator (RSSI)-based method during our field test.Comment: Submitted to IEEE/IEIE ICCE-Asia 202

A Radio-fingerprinting-based Vehicle Classification System for Intelligent Traffic Control in Smart Cities

The measurement and provision of precise and upto-date traffic-related key performance indicators is a key element and crucial factor for intelligent traffic controls systems in upcoming smart cities. The street network is considered as a highly-dynamic Cyber Physical System (CPS) where measured information forms the foundation for dynamic control methods aiming to optimize the overall system state. Apart from global system parameters like traffic flow and density, specific data such as velocity of individual vehicles as well as vehicle type information can be leveraged for highly sophisticated traffic control methods like dynamic type-specific lane assignments. Consequently, solutions for acquiring these kinds of information are required and have to comply with strict requirements ranging from accuracy over cost-efficiency to privacy preservation. In this paper, we present a system for classifying vehicles based on their radio-fingerprint. In contrast to other approaches, the proposed system is able to provide real-time capable and precise vehicle classification as well as cost-efficient installation and maintenance, privacy preservation and weather independence. The system performance in terms of accuracy and resource-efficiency is evaluated in the field using comprehensive measurements. Using a machine learning based approach, the resulting success ratio for classifying cars and trucks is above 99%

Beam Tracking Strategies for 5G New Radio Networks Operating in the Millimetre Wave Bands

[ES] La llegada de la próxima generación del estándar de comunicaciones móviles, la llamada quinta generación (5G), es prácticamente una realidad. Las primeras redes comerciales han comenzado a ser desplegadas, centrándose en ofrecer altas velocidades de transferencia de datos. Sin embargo, el estándar 5G va mucho más allá y prevé dar soporte a nuevos servicios que pretenden revolucionar la sociedad. Estos nuevos servicios imponen un nivel alto de requisitos en no solo en cuanto a velocidad del tráfico de datos, sino en cuanto a latencia o número de dispositivos conectados simultáneamente. La amplia variedad de requisitos no puede ser soportada por las redes de cuarta generación (4G), por lo que se hizo necesario plantear un nuevo paradigma para las redes inalámbricas. Con la promesa de grandes cantidades de ancho de banda sin utilizar, el estándar 5G contempla utilizar frecuencias en la comúnmente conocida como banda de milimétricas (mmWave). Esta banda presenta grandes pérdidas de propagación, que se acentúan si existen bloqueos de señal. Actividades regulatorias del uso de las bandas de milimétricas atrajo el interés tanto de la industria como de la academia en plantear soluciones para dar servicio en estas bandas. En los últimos años se han presentado infinidad de trabajos basados en sistemas con múltiples antenas o MIMO, para conformar las señales transmitidas o recibidas en haces apuntando en determinadas direcciones. La ganancia que aportan los sistemas MIMO pueden compensar las altas pérdidas de propagación, asegurando la viabilidad de las comunicaciones mmWave. Se ha detectado una evidente falta de estudios sobre la viabilidad de sistemas MIMO en entornos móviles y dinámicos con bloqueos que hagan necesario que el sistema se reconfigure. Esta Tesis pretende cubrir este espacio desde un enfoque práctico y propone mecanismos de gestión de los haces para hacerles un seguimiento utilizando los recursos y mecanismos del nuevo estándar 5G. Las soluciones aportadas se basan en el uso eficiente de los reportes de medidas de las señales de referencia estandarizadas en enlace descendente. En primer lugar, esta Tesis recoge un análisis minucioso del estado del arte, donde se corrobora la necesidad de aportar soluciones de seguimiento de haces en sistemas de comunicaciones en la banda de milimétricas. Además, se estudian los diferentes mecanismos definidos en el estándar 5G y que posibilitan el seguimiento. Cabe destacar que el estándar no define un mecanismo único a seguir, permitiendo presentar propuestas. Una vez conocidas las tecnologías, se centra el estudio en el impacto del seguimiento sobre las prestaciones a nivel de red y de enlace. Dicho estudio se realiza sobre un sistema punto a punto, donde el terminal móvil se desplaza por un entorno urbano. En base a simulaciones de red, se cuantifica el índice de seguimiento de haz y de cómo dicho seguimiento afecta a la relación señal a ruido más interferencia (SINR) y la tasa de transmisión del usuario. Las soluciones de seguimiento propuestas en esta Tesis se pueden clasificar en dos categorías. En una primera categoría, se realiza el seguimiento en base a reportes de medidas de las señales de referencia. Independientemente de la velocidad, se alcanza un seguimiento del 91% con poca penalización en la tasa de transmisión si se monitorizan los haces de interés con una periodicidad menor de 20 ms. En la segunda categoría caben mecanismos de seguimiento que hacen uso de fuentes externas de información. Dentro de esta categoría, se propone un fingerprinting que relacione haces con la localización reportada y un modelo de machine learning (ML) que prediga los haces a utilizar. El fingerprinting proporciona los mismos niveles de rendimiento. Sin embargo, esta solución es muy sensible a errores y requiere considerar todos los casos posibles, lo que la hace tecnológicamente inviable. En cambio, el modelo de ML, que hace p[CA] L'arribada de la següent generació de l'estàndard de comunicacions mòbils, l'anomenada cinquena generació (5G), es pràcticament una realitat. Les primeres xarxes comercials han començat a desplegar-se i s'han centrat en oferir altes velocitats de transferència de dades. No obstant, l'estàndard 5G va molt mes allà y preveu donar suport a nous serveis que pretenen revolucionar la societat. Estos nous serveis imposen un alt nivell de requisits no sols en quant a velocitat de tràfic de dades, si no també en quant a latència o número de connexions simultànies. L'ampla varietat de requisits no es suportada per les xarxes de quarta generació (4G) actuals, per el qual es va fer necessari un nou paradigma de xarxes sense fil. Amb la promesa de amplies quantitats d'ample de banda, l'estàndard 5G contempla utilitzar freqüències a la banda de mil·limètriques. Esta banda presenta l'inconvenient d'experimentar grans pèrdues de propagació, que s'accentuen en cas de bloqueigs. L'apertura de les bandes de mil·limètriques va atraure l'interès tant de l'industria com de l'acadèmia en plantejar solucions per a donar servei en estes bandes. En els últims anys s'han presentat infinitat de treballs basats en sistemes amb múltiples antenes o MIMO, per a conformar els senyals transmesos o rebuts en feixos apuntant en determinades direccions d'interès. El guany de feix es pot utilitzar per a compensar les pèrdues de propagació, assegurant la viabilitat de les comunicacions en la banda de mil·limètriques. No obstant això, s'ha detectat una preocupant manca d'estudis sobre la viabilitat d'estos sistemes en entorns mòbils i dinàmics, amb obstacles que bloquejen els feixos i facen necessari que el sistema es reconfigure. El present treball de Tesi pretén cobrir este espai buit i des d'un punt de vista pràctic, es proposen mecanismes de gestió dels feixos per a ser el seguiment utilitzant els recursos i mecanismes dels que disposa l'estàndard 5G. D'esta manera, les solucions aportades es basen en la utilització eficient dels reports de mesures dels senyals de referència del enllaç descendent. En primer lloc, esta Tesi recull una anàlisi minuciosa de l'estat de l'art on es corrobora la necessitat de aportar solucions de seguiment de feixos per a comunicacions en la banda de freqüències mil·limètriques. A més a més, s'estudien els diferents mecanismes definits a l'estàndard 5G i que possibiliten el seguiment. Cap destacar que l'estàndard no defineix un mecanisme únic, si no que deixa la porta oberta a presentar propostes. Una vegada conegudes les tecnologies, l'estudi es centra en l'impacte del seguiment sobre les prestacions a nivell de xarxa i d'enllaç. Este estudi es realitza sobre un sistema MIMO punt a punt, en una única estació base i un terminal mòbil desplaçant-se en un entorn urbà. En base a simulacions d'extrem a extrem, es quantifica l'índex de seguiment de feix i com l'anomenat seguiment afecta a la relació senyal a soroll més interferència (SINR) i a la taxa instantània de transmissió de l'usuari. Les solucions de seguiment de feixos propostes a la Tesi es poden classificar en dos categories. A la primera categoria, el seguiment de feixos es realitza en base als reports de mesures dels senyals de referència. Independentment de la velocitat, s'arriba a una taxa de seguiment del 91% amb poca penalització de taxa de transmissió si els feixos d'interès es mesuren amb una periodicitat menor a 20 ms. A la segona categoria pertanyen els algoritmes que utilitzen fonts d'informació externes. Dins d'aquesta categoria es proposa un fingerprinting que relaciona un parell de feixos amb la ubicació de l'usuari, i a banda un model d'intel·ligència artificial (IA) que preveu el feix a utilitzar. El fingerprinting ofereix el mateix rendiment. Però, esta solució es molt sensible a errors i requereix considerar tots els casos possibles, fent-la tecnològicament inviable. En canvi, el[EN] The arrival of the next generation of mobile communication standards, the so-called Fifth Generation (5G), is already a reality. The first commercial networks have begun to be deployed, and they focus on providing higher data rates. However, the 5G standard goes much further from that and aims at providing support to new services which will revolutionise the society. These new services impose a high level of requirements not only in terms of the data traffic speed, but also in terms of very low latency or incredibly large number of simultaneous connections. This wide variety of requirements cannot be technologically supported by the current Fourth Generation (4G) networks, so it became necessary to move forward with a new paradigm for wireless networks. With the promise of large amounts of bandwidth, in the order of GHz, the 5G standard contemplates the use of frequencies in the commonly known Millimetre Wave (mmWave) band. The mmWave band experiences large propagation losses, which are accentuated in blockage events. Regulatory activities worldwide in the mmWave bands attracted the interest of both the industry and the academia. In the last few years, a tremendous number of contributions on mmWave propagation studies and networks have appeared, most of them based on Multiple-Input Multiple-Output (MIMO) solutions. MIMO architectures allow to beamform, which focuses the radiated energy on certain directions of interest called beams. The additional beam gain compensates the high propagation losses, ensuring the viability of the communications in the mmWave band. There is an evident lack of viability studies of mmWave MIMO systems in mobile and highly-dynamic environments, where obstacles may block beams and forcing frequent re-configurations. This Thesis work aims to fill this gap from a practical approach. This Thesis proposes beam management mechanisms utilising the mechanisms and resources offered by the Third Generation Partnership Project (3GPP) 5G radio access standard: 5G New Radio (NR). The practical solutions are based on the efficient use of measurement reports of standardised downlink Reference Signals (RS). In first place, this Thesis provides a thorough state-of-the-art analysis and corroborates the need of adopting beam tracking solutions for mmWave networks. Then, a complete overview of the 5G standard mechanisms that enable beam tracking is given. The NR standard does not define a standardised mechanism for beam tracking, leaving the door open to proposals to carry out such monitoring. Once the technologies have been identified, the Thesis continues with assessing the impact of the beam tracking strategies on the network and link-level performance. The study is focused on individual point-to-point mmWave links in a realistic urban environment. Based on end-to-end network simulations, the Thesis is interested in assessing the beam tracking success ratio and how beam misalignment affects the perceived Signal to Noise plus Interference Ratio (SINR) and user throughput at pedestrian and vehicular speeds. The beam tracking solutions proposed in this Thesis fall into two categories. The first category monitors beams based on measuring and reporting beamformed RS. Regardless of the speed, this beam tracking category provides up to 91 % tracking performance, with little throughput reduction if the beams of interest are measured with a periodicity below 20 ms. Beam tracking in the second category relies on external information sources. Within this category, this Thesis proposes a fingerprinting database relating beams to the user position and a machine learning (ML) model. Fingerprinting beam tracking is technologically viable and provides similar performance levels. However, this solution is very sensitive to errors and requires considering all possible situations. The ML beam tracking, which makes predictions with a 16 % of estimation error for the reference data set.I want to thank the Spanish Ministry of Education and Professional Formation for funding this Thesis work with an official pre-doctoral contract grant.Herranz Claveras, C. (2019). Beam Tracking Strategies for 5G New Radio Networks Operating in the Millimetre Wave Bands [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/130845TESI

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Location Privacy in LTE: A Case Study on Exploiting the Cellular Signaling Plane's Timing Advance

Location privacy is an oft-overlooked, but exceedingly important niche of the overall privacy macrocosm. An ambition of this work is to raise awareness of concerns relating to location privacy in cellular networks. To this end, we will demonstrate how user location information is leaked through a vulnerability, viz. the timing advance (TA) parameter, in the Long Term Evolution (LTE) signaling plane and how the position estimate that results from that parameter can be refined through a previously introduced method called Cellular Synchronization Assisted Refinement (CeSAR) [1]. With CeSAR, positioning accuracies that meet or exceed the FCC’s E-911 mandate are possible making CeSAR simultaneously a candidate technology for meeting the FCC’s wireless localization requirements and a demonstration of the alarming level of location information sent over the air. We also introduce a geographically diverse data set of TAs collected from actual LTE network implementations utilizing different cell phone chipsets. With this data set we show the appropriateness of modeling the error associated with a TA as normally distributed.

Neural Network-Based Ranging with LTE Channel Impulse Response for Localization in Indoor Environments

A neural network (NN)-based approach for indoor localization via cellular long-term evolution (LTE) signals is proposed. The approach estimates, from the channel impulse response (CIR), the range between an LTE eNodeB and a receiver. A software-defined radio (SDR) extracts the CIR, which is fed to a long short-term memory model (LSTM) recurrent neural network (RNN) to estimate the range. Experimental results are presented comparing the proposed approach against a baseline RNN without LSTM. The results show a receiver navigating for 100 m in an indoor environment, while receiving signals from one LTE eNodeB. The ranging root-mean squared error (RMSE) and ranging maximum error along the receiver's trajectory were reduced from 13.11 m and 55.68 m, respectively, in the baseline RNN to 9.02 m and 27.40 m, respectively, with the proposed RNN-LSTM.Comment: Submitted to ICCAS 202