936 research outputs found
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
The Internet of Things (IoT) has started to empower the future of many
industrial and mass-market applications. Localization techniques are becoming
key to add location context to IoT data without human perception and
intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN)
technologies have advantages such as long-range, low power consumption, low
cost, massive connections, and the capability for communication in both indoor
and outdoor areas. These features make LPWAN signals strong candidates for
mass-market localization applications. However, there are various error sources
that have limited localization performance by using such IoT signals. This
paper reviews the IoT localization system through the following sequence: IoT
localization system review -- localization data sources -- localization
algorithms -- localization error sources and mitigation -- localization
performance evaluation. Compared to the related surveys, this paper has a more
comprehensive and state-of-the-art review on IoT localization methods, an
original review on IoT localization error sources and mitigation, an original
review on IoT localization performance evaluation, and a more comprehensive
review of IoT localization applications, opportunities, and challenges. Thus,
this survey provides comprehensive guidance for peers who are interested in
enabling localization ability in the existing IoT systems, using IoT systems
for localization, or integrating IoT signals with the existing localization
sensors
A Localization System for Optimizing the Deployment of Small Cells in 2-Tier Heterogeneous Wireless Networks
Due to the ever growing population of mobile device users and expansion on the number of devices and applications requiring data usage, there is an increasing demand for improved capacity in wireless cellular networks. Cell densification and 2-tier heterogeneous networks (HetNets) are two solutions which will assist 5G systems in meeting these growing capacity demands. Small-cell deployment over existing heterogeneous networks have been considered
by researchers. Different strategies for deploying these small-cells within the existing network among which are random, cell-edge and high user concentration (HUC) have also been explored. Small cells deployed on locations of HUC offloads traffic from existing network infrastructure, ensure good Quality of Service (QoS) and balanced load in the network but there is a challenge of identifying HUC locations.
There has been considerable research performed into techniques for determining user location and cell deployment. Currently localization can be achieved using time dependent methods such as Time of Arrival (ToA), Time Difference of Arrival (TDoA), or Global Positioning Systems (GPS). GPS based solutions provide high accuracy user positioning but suffer from concerns over user privacy, and other time dependent approaches require
regular synchronization which can be difficult to achieve in practice. Alternatively, Received Signal Strength (RSS) based solutions can provide simple anonymous user data, requiring no extra hardware within the mobile handset but often rely on triangulation from adjacent Base Stations (BS). In mobile cellular networks such solutions are therefore often only applicable near the cell edge, as installing additional BS would increase the complexity and cost of a network deployment.
The work presented in this thesis overcomes these limitations by providing an observer system for wireless networks that can be used to periodically monitor the cell coverage area and identify regions of high concentrations of users for possible small cell deployment in 2-tier heterogeneous networks. The observer system comprises of two collinear antennas separated by λ/2. The relative phase of each antenna was varied using a phase shifter so that the combined output of the two antennas were used to create sum and difference radiation
patterns, and to steer the antenna radiation pattern creating different azimuth positions for AoA estimation. Statistical regression analysis was used to develop range estimation models based on four different environment empirical pathloss models for user range estimation. Users were located into clusters by classifying them into azimuth-range classes and counting the number of users in each class. Locations for small cell deployment were identified based on class population. BPEM, ADEM, BUEM, EARM and NLOS models were developed for more accurate range estimation. A prototype system was implemented and
tested both outdoor and indoor using a network of WiFi nodes. Experimental results show close relationship with simulation and an average PER in range estimation error of 80% by applying developed error models. Based on both simulation and experiment, system showed good performance.
By deploying micro-, pico-, or femto-cells in areas of higher user concentration, high data rates and good quality of service in the network can be maintained. The observer system provides the network manager with relative angle of arrival (AoA), distance estimation and
relative location of user clusters within the cell. The observer system divides the cell into a series of azimuthal and range sectors, and determines which sector the users are located in. Simulation and a prototype design of the system is presented and results have shown system robustness and high accuracy for its purpose
A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives
Efficient localization plays a vital role in many modern applications of
Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would
contribute to improved control, safety, power economy, etc. The ubiquitous 5G
NR (New Radio) cellular network will provide new opportunities for enhancing
localization of UAVs and UGVs. In this paper, we review the radio frequency
(RF) based approaches for localization. We review the RF features that can be
utilized for localization and investigate the current methods suitable for
Unmanned vehicles under two general categories: range-based and fingerprinting.
The existing state-of-the-art literature on RF-based localization for both UAVs
and UGVs is examined, and the envisioned 5G NR for localization enhancement,
and the future research direction are explored
5G and beyond networks
This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications
Posicionamento cooperativo para redes sem fios heterogéneas
Doutoramento em Engenharia ElectrotécnicaFuture emerging market trends head towards positioning based services
placing a new perspective on the way we obtain and exploit positioning
information. On one hand, innovations in information technology and
wireless communication systems enabled the development of numerous
location based applications such as vehicle navigation and tracking,
sensor networks applications, home automation, asset management,
security and context aware location services. On the other hand, wireless
networks themselves may bene t from localization information to
improve the performances of di erent network layers. Location based
routing, synchronization, interference cancellation are prime examples
of applications where location information can be useful.
Typical positioning solutions rely on measurements and exploitation of
distance dependent signal metrics, such as the received signal strength,
time of arrival or angle of arrival. They are cheaper and easier to implement
than the dedicated positioning systems based on ngerprinting,
but at the cost of accuracy. Therefore intelligent localization algorithms
and signal processing techniques have to be applied to mitigate
the lack of accuracy in distance estimates. Cooperation between nodes
is used in cases where conventional positioning techniques do not perform
well due to lack of existing infrastructure, or obstructed indoor
environment. The objective is to concentrate on hybrid architecture
where some nodes have points of attachment to an infrastructure, and
simultaneously are interconnected via short-range ad hoc links. The
availability of more capable handsets enables more innovative scenarios
that take advantage of multiple radio access networks as well as
peer-to-peer links for positioning.
Link selection is used to optimize the tradeo between the power consumption
of participating nodes and the quality of target localization.
The Geometric Dilution of Precision and the Cramer-Rao Lower Bound
can be used as criteria for choosing the appropriate set of anchor nodes
and corresponding measurements before attempting location estimation
itself. This work analyzes the existing solutions for node selection
in order to improve localization performance, and proposes a novel
method based on utility functions. The proposed method is then extended
to mobile and heterogeneous environments. Simulations have
been carried out, as well as evaluation with real measurement data. In
addition, some speci c cases have been considered, such as localization
in ill-conditioned scenarios and the use of negative information.
The proposed approaches have shown to enhance estimation accuracy,
whilst signi cantly reducing complexity, power consumption and signalling
overhead.As tendências nos mercados emergentes caminham na direção dos serviços baseados em posicionamento, criando uma nova perspectiva na forma como podemos obter e utilizar informação de posicionamento.
Por um lado, as inovações em tecnologias da informação e sistemas de comunicação sem fios permitiram o desenvolvimento de inúmeras aplicações baseadas em localização, tais como a navegação e monitorização de veículo, aplicações de redes de sensores, domótica, gestão de ativos, segurança e serviços de localização sensíveis ao contexto. Por outro lado, as próprias redes sem fios podem beneficiar da informação de localização dos utilizadores de forma a melhorarem as performances de diferentes camadas de rede. Routing baseado em localização, sincronização e cancelamento de interferência são os exemplos mais representativos de áreas onde a informação de localização pode ser útil.
Soluções de localização típicas dependem de medições e de aproveitamento de métricas de sinal dependentes da distância, tais como a potência do sinal recebido, o tempo ou ângulo de chegada. São mais baratos e fáceis de implementar do que sistemas de localização dedicados com base em fingerprinting, com a desvantagem da perda de precisão. Consequentemente, algoritmos inteligentes de localização e técnicas de processamento de sinal têm de ser aplicados para compensar a falta de precisão das estimativas de distância. A cooperação entre nodos é usada nos casos em que as técnicas convencionais de posicionamento não têm um bom desempenho devido à inexistência de infraestrutura adequada, ou a um ambiente interior com obstruções.
O objetivo é ter uma arquitetura híbrida, onde alguns nós têm pontos de ligação a uma infraestrutura e simultaneamente estão interligados através ligações ad-hoc de curto alcance. A disponibilidade de equipamentos mais capazes permite cenários mais inovadores que tiram proveito de múltiplas redes de acesso de rádio, bem como ligações peer-to-peer, para o posicionamento.
A seleção de ligações é usada para otimizar o equilíbrio entre o consumo
de energia dos nós participantes e da qualidade da localização do alvo. A diluição geométrica de precisão e a Cramér Rao Lower Bound podem ser utilizadas como critrio para a escolha do conjunto adequado de nodos de ancoragem e as medições correspondentes antes de realizar a tarefa de estimativa de localizaçãoo. Este trabalho analisa as soluções existentes para a seleção de nós, a fim de melhorar o desempenho de localização e propõe um novo método baseado em funções de utilidade.
O método proposto é então estendido para ambientes móveis e heterogéneos. Foram realizadas simulações bem como avaliação de dados de medições reais. Além disso, alguns casos específicos foram considerados, tais como a localização em cenários mal-acondicionados e uso de informação negativa. As abordagens propostas revelaram uma melhoria na precisão da estimação, ao mesmo tempo que reduziram significativamente a complexidade do cálculo, o consumo de energia e o overhead do sinal
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