611 research outputs found

    Target Tracking in Confined Environments with Uncertain Sensor Positions

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    To ensure safety in confined environments such as mines or subway tunnels, a (wireless) sensor network can be deployed to monitor various environmental conditions. One of its most important applications is to track personnel, mobile equipment and vehicles. However, the state-of-the-art algorithms assume that the positions of the sensors are perfectly known, which is not necessarily true due to imprecise placement and/or dropping of sensors. Therefore, we propose an automatic approach for simultaneous refinement of sensors' positions and target tracking. We divide the considered area in a finite number of cells, define dynamic and measurement models, and apply a discrete variant of belief propagation which can efficiently solve this high-dimensional problem, and handle all non-Gaussian uncertainties expected in this kind of environments. Finally, we use ray-tracing simulation to generate an artificial mine-like environment and generate synthetic measurement data. According to our extensive simulation study, the proposed approach performs significantly better than standard Bayesian target tracking and localization algorithms, and provides robustness against outliers.Comment: IEEE Transactions on Vehicular Technology, 201

    Whitepaper on New Localization Methods for 5G Wireless Systems and the Internet-of-Things

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    Application of Channel Modeling for Indoor Localization Using TOA and RSS

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    Recently considerable attention has been paid to indoor geolocation using wireless local area networks (WLAN) and wireless personal area networks (WPAN) devices. As more applications using these technologies are emerging in the market, the need for accurate and reliable localization increases. In response to this need, a number of technologies and associated algorithms have been introduced in the literature. These algorithms resolve the location either by using estimated distances between a mobile station (MS) and at least three reference points (via triangulation) or pattern recognition through radio frequency (RF) fingerprinting. Since RF fingerprinting, which requires on site measurements is a time consuming process, it is ideal to replace this procedure with the results obtained from radio channel modeling techniques. Localization algorithms either use the received signal strength (RSS) or time of arrival (TOA) of the received signal as their localization metric. TOA based systems are sensitive to the available bandwidth, and also to the occurrence of undetected direct path (UDP) channel conditions, while RSS based systems are less sensitive to the bandwidth and more resilient to UDP conditions. Therefore, the comparative performance evaluation of different positioning systems is a multifaceted and challenging problem. This dissertation demonstrates the viability of radio channel modeling techniques to eliminate the costly fingerprinting process in pattern recognition algorithms by introducing novel ray tracing (RT) assisted RSS and TOA based algorithms. Two sets of empirical data obtained by radio channel measurements are used to create a baseline for comparative performance evaluation of localization algorithms. The first database is obtained by WiFi RSS measurements in the first floor of the Atwater Kent laboratory; an academic building on the campus of WPI; and the other by ultra wideband (UWB) channel measurements in the third floor of the same building. Using the results of measurement campaign, we specifically analyze the comparative behavior of TOA- and RSS-based indoor localization algorithms employing triangulation or pattern recognition with different bandwidths adopted in WLAN and WPAN systems. Finally, we introduce a new RT assisted hybrid RSS-TOA based algorithm which employs neural networks. The resulting algorithm demonstrates a superior performance compared to the conventional RSS and TOA based algorithms in wideband systems

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

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    [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 Outdoor Localization Using Radio Maps: A Deep Learning Approach

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    Global Navigation Satellite Systems typically perform poorly in urban environments, where the likelihood of line-of-sight conditions between the devices and the satellites is low, and thus alternative localization methods are required for good accuracy. We present LocUNet: A convolutional, end-to-end trained neural network for the localization task, able to estimate the position of a user from the received signal strength (RSS) from a small number of Base Stations (BSs). In the proposed method, the user to be localized simply reports the measured RSS to a central processing unit, which may be located in the cloud. Using estimations of pathloss radio maps of the BSs and the RSS measurements, LocUNet can localize users with state-of-the-art accuracy and enjoys high robustness to inaccuracies in the estimations of radio maps. The proposed method does not require pre-sampling of new environments and is suitable for real-time applications. Moreover, two novel datasets that allow for numerical evaluations of RSS and ToA methods in realistic urban environments are presented and made publicly available for the research community. By using these datasets, we also provide a fair comparison of state-of-the-art RSS and ToA-based methods in the dense urban scenario and show numerically that LocUNet outperforms all the compared methods.Comment: Submitted to IEEE Transactions on Wireless Communication

    Potentials of Deterministic Radio Propagation Simulation for AI-Enabled Localization and Sensing

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    Machine leaning (ML) and artificial intelligence (AI) enable new methods for localization and sensing in next-generation networks to fulfill a wide range of use cases. These approaches rely on learning approaches that require large amounts of training and validation data. This paper addresses the data generation bottleneck to develop and validate such methods by proposing an integrated toolchain based on deterministic channel modeling and radio propagation simulation. The toolchain is demonstrated exemplary for scenario classification to obtain localization-related channel parameters within an aircraft cabin environment
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