Performance Analysis of Hybrid 5G-GNSS Localization

\ua9 2018 IEEE. We consider a novel positioning solution combining millimeter wave (mmW) 5G and Global Navigation Satellite System (GNSS) technologies. The study is carried out theoretically by deriving the Fisher Information Matrix (FIM) of a combined 5G-GNSS positioning system and, subsequently, the position, rotation and clock-bias error lower bounds. We pursue a two-step approach, namely, computing first the FIM for the channel parameters, and then transforming it into the FIM of the position, rotation and clock-bias. The analysis shows advantages of the hybrid positioning in terms of i) localization accuracy, ii) coverage, iii) precise rotation estimation and iv) clock-error estimation. In other words, we demonstrate that a tight coupling of the two technologies can provide mutual benefits

Attitude Determination in Urban Canyons: A Synergy between GNSS and 5G Observations

This paper considers the attitude determination problem based on the global navigation satellite system (GNSS) and fifth-generation (5G) measurement fusion to address the shortcomings of standalone GNSS and 5G techniques in deep urban regions. The tight fusion of the GNSS and the 5G observations results in a unique hybrid integer- and orthonormality-constrained optimization problem. To solve this problem, we propose an estimation method consisting of the steps of float solution computation, ambiguity resolution, and fixed solution computation. Numerical results reveal that the proposed method can effectively improve the attitude determination accuracy and reliability compared to either the pure GNSS solution or the pure 5G solution

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

Robust Location-Aided Beam Alignment in Millimeter Wave Massive MIMO

Location-aided beam alignment has been proposed recently as a potential approach for fast link establishment in millimeter wave (mmWave) massive MIMO (mMIMO) communications. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE seek coordination on the basis of correlated yet individual position information. We formulate the optimum beam alignment solution as the solution of a Bayesian team decision problem. We then propose a suite of algorithms to approach optimality with reduced complexity. The effectiveness of the robust beam alignment procedure, compared with classical designs, is then verified on simulation settings with varying location information accuracies.Comment: 24 pages, 7 figures. The short version of this paper has been accepted to IEEE Globecom 201

Grid-based Hybrid 3DMA GNSS and Terrestrial Positioning

The paper discusses the increasing use of hybridized sensor information for GNSS-based localization and navigation, including the use of 3D map-aided GNSS positioning and terrestrial systems based on different geometric measurement principles. However, both GNSS and terrestrial systems are subject to negative impacts from the propagation environment, which can violate the assumptions of conventionally applied parametric state estimators. Furthermore, dynamic parametric state estimation does not account for multi-modalities within the state space leading to an information loss within the prediction step. In addition, the synchronization of non-deterministic multi-rate measurement systems needs to be accounted. In order to address these challenges, the paper proposes the use of a non-parametric filtering method, specifically a 3DMA multi-epoch Grid Filter, for the tight integration of GNSS and terrestrial signals. Specifically, the fusion of GNSS, Ultra-wide Band (UWB) and vehicle motion data is introduced based on a discrete state representation. Algorithmic challenges, including the use of different measurement models and time synchronization, are addressed. In order to evaluate the proposed method, real-world tests were conducted on an urban automotive testbed in both static and dynamic scenarios. We empirically show that we achieve sub-meter accuracy in the static scenario by averaging a positioning error of $0.64$ m, whereas in the dynamic scenario the average positioning error amounts to $1.62$ m. The paper provides a proof-of-concept of the introduced method and shows the feasibility of the inclusion of terrestrial signals in a 3DMA positioning framework in order to further enhance localization in GNSS-degraded environments

Bidirectional UWB Localization: A Review on an Elastic Positioning Scheme for GNSS-deprived Zones

A bidirectional Ultra-Wideband (UWB) localization scheme is one of the three widely deployed design integration processes ordinarily destined for time-based UWB positioning systems. The key property of the bidirectional UWB localization is its ability to serve both the navigation and tracking assignments on-demand within a single localization scheme. Conventionally, the perspective of navigation and tracking in wireless localization systems is viewed distinctly as an individual system because different methodologies were required for the implementation process. The ability to flexibly or elastically combine two unique positioning perspectives (i.e., navigation and tracking) within a single scheme is a paradigm shift in the way location-based services are observed. Thus, this article addresses and pinpoints the potential of a bidirectional UWB localization scheme. Regarding this, the complete system model of the bidirectional UWB localization scheme was comprehensively described based on modular processes in this article. The demonstrative evaluation results based on two system integration processes as well as a SWOT (strengths, weaknesses, opportunities, and threats) analysis of the scheme were also discussed. Moreover, we argued that the presented bidirectional scheme can also be used as a prospective topology for the realization of precise location estimation processes in 5G/6G wireless mobile networks, as well as Wi-Fi fine-time measurement-based positioning systems in this article.Comment: 30 pages, 12 figure

Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks

Cooperative Positioning using Massive Differentiation of GNSS Pseudorange Measurements

With Differential GNSS (DGNSS), Single Differentiation (SD) of GNSS pseudorange mea- surements is computed with the aim of correcting harmful errors such as ionospheric and tropospheric delays. These errors can be mitigated to up to very few centimeters, which denotes a performance improvement with respect to the Standard Point Positioning (SPP) solution, widely used in GNSS receivers. However, with DGNSS it is necessary to have a very precise knowledge of the coordinates of a reference station in order to experience this performance improvement. We propose the Massive User-Centric Single Differentiation (MUCSD) algorithm, which is proven to have a comparable performance to DGNSS with- out the need of a reference station. Instead, N cooperative receivers which provide noisy observations of their position and clock bias are introduced in the model. The MUCSD algorithm is mathematically derived with an Iterative Weighted Least Squares (WLS) Estimator. The estimator lower bound is calculated with the Cramér-Rao Bound (CRB). Several scenarios are simulated to test the MUCSD algorithm with the MassiveCoop-Sim simulator. Results show that if the observations provided by the cooperative users have a noise of up to 10 meters, DGNSS performance can be obtained with N = 10. When observations are very noisy, the MUCSD performance still approaches DGNSS for high values of N

Design and implementation of a positioning service in the context of smart cities

In recent decades, cities have become the global hubs of commerce, culture, science and society, being also the largest consumers of energy and the largest carbon emitters. With the objective of solving this problem, sustainable cities or "Smart Cities" are one of the objectives to be fulfilled in the 2030 Agenda. With this objective in mind and in the context of the project "Navigation and GNSS in Smart Cities -Testbed Concept Definition" (HANSEL), the student intends to design and develop a service in charge of sensor positioning based on GNSS and Cellular technologies for the subsequent treatment of the information generated for various purposes, such as the detection and location of sources of interference or GNSS and Cellular hybridization, obtaining hybrid positions, more precise than those of each system separately. This system or service is intended to be accessible to the general public via Internet (as a Software as a Service orSaaS), and takes advantage of the all the features cloud computing has to offer, both at performance and energy consumption level.En les últimes dècades, les ciutats s'han convertit en els nuclis mundials de comerç, cultura, ciència i societat, sent també les majors consumidores d'energia i les més grans emissores de carboni. Amb l'objectiu de solucionar aquesta problemàtica, les ciutats sostenibles o "SmartCities" són un dels objectius a complir en l'Agenda 2030. Amb aquest objectiu en ment i en el context del projecte "Navigation and GNSS in Smart Cities - Testbed Concept Definition"(HANSEL), l'estudiant pretén dissenyar i desenvolupar un servei a càrrec del posicionament de sensors basats en tecnologies GNSS i cel·lular per al posterior tractament de la informació generada per a diverses finalitats, com la detecció i localització de fonts d'interferència o la hibridació GNSS i cel·lular, donant lloc a posicions híbrides, més precises que les de cada sistema per separat. Aquest servei pretén ser accessible mitjançant Internet al públic general (com un Software com a servei o SaaS), i aprofita els avantatges que la computació en el núvol és capaç d'oferir tant a nivell de prestacions com a nivell d'estalvi d'energia respecte als dispositius de navegació actuals.En las últimas décadas, las ciudades se han convertido en los núcleos mundiales de comercio, cultura, ciencia y sociedad, siendo también las mayores consumidoras de energía y las más grandes emisoras de carbono. Con el objetivo de solucionar esta problemática, las ciudades sostenibles o "Smart Cities" son uno de los objetivos a cumplir en la Agenda 2030. Con este objetivo en mente y en el contexto del proyecto "Navigation and GNSS in Smart Cities - Testbed Concept Definition" (HANSEL), el estudiante pretende diseñar y desarrollar un servicio a cargo del posicionamiento de sensores basados en tecnologías GNSS y celular para el posterior tratamiento de la información generada para diversos fines, como la detección y localización de fuentes de interferencia o la hibridación GNSS y celular, dando lugar a posiciones híbridas, más precisas que las de cada sistema por separado. Dicho servicio pretende ser accesible mediante Internet al público general (como un Software como servicio o SaaS), y aprovecha las ventajas que la computación en la nube es capaz de ofrecer tanto a nivel de prestaciones como a nivel de ahorro de energía con respecto a los dispositivos de navegación actuales