Efficient Ambient LoRa Backscatter with On-Off Keying Modulation

Backscatter communication holds potential for ubiquitous and low-cost connectivity among low-power IoT devices. To avoid interference between the carrier signal and the backscatter signal, recent works propose a frequency-shifting technique to separate these two signals in the frequency domain. Such proposals, however, have to occupy the precious wireless spectrum that is already overcrowded, and increase the power, cost, and complexity of the backscatter tag. In this paper, we revisit the classic ON-OFF Keying (OOK) modulation and propose Aloba, a backscatter system that takes the ambient LoRa transmissions as the excitation and piggybacks the in-band OOK modulated signals over the LoRa transmissions. Our design enables the backsactter signal to work in the same frequency band of the carrier signal, meanwhile achieving flexible data rate at different transmission range. The key contributions of Aloba include: (1) the design of a low-power backscatter tag that can pick up the ambient LoRa signals from other signals. (2) a novel decoding algorithm to demodulate both the carrier signal and the backscatter signal from their superposition. We further adopt link coding mechanism and interleave operation to enhance the reliability of backscatter signal decoding. We implement Aloba and conduct head-to-head comparison with the state-of-the-art LoRa backscatter system PLoRa in various settings. The experiment results show Aloba can achieve 199.4 Kbps data rate at various distances, 52.4 times higher than PLoRa

Wireless communication, sensing, and REM: A security perspective

The diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell

EVGA Japan co-operation report : Ochanomizu Research Visit 2014

Three researchers from Japan worked on the EVGA project during the fall 2014. Joni Jämsä (M.Sc.) planned tasks for them based on the resumes they sent before arriving in Ylivieska. Tasks included mobile programming, user interfaces, and data visualizing. Detailed job descriptions included working on an acoustic measurement system based on iProtoxi processors, performing a technology review about intelligent traffic in Japanese technology, and working on a user interface design developed for the weather station and the electric vehicle measurement system (NES). The research visit lasted eight weeks

Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key "ingredient" to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases

Autonomous Sensing Nodes for IoT Applications

The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [μW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented. Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Exploiting PHY for improving LoRa based communication and localisation system

LoRa is an emerging technology of low-power wide-area networks (LPWANs) operating on industrial, scientific and medical (ISM) bands to provide connectivity for Internet of Thing (IoT) devices. As the number of devices increases, the network suffers from scalability issues. Therefore, we design a cloud radio access network (C-RAN or Cloud-RAN) with multiple LoRa gateways to solve this problem. Furthermore, we develop novel algorithms to provide accurate localisation for LoRa devices. This thesis makes three new contributions to LoRa based communication and localisation system as follows. The first contribution is a compressive sensing-based algorithm to reduce the uplink bit rate between the gateways and the cloud server. The proposed novel compression algorithm can reduce the bandwidth usage for the fronthaul without decreasing LoRa packet delivery rates. Our evaluation shows that with four gateways up to 87.5% PHY samples can be compressed and 1.7x battery life for end devices can be achieved. The second contribution is a novel algorithm to improve the resolution of the radio signals for localisation. The proposed algorithm synchronises multiple non-overlapped communication channels by exploiting the unique features of the LoRa radio to increase the overall bandwidth. We evaluate its performance in an outdoor area of 100 m × 60 m, which shows a median error of 4.4 m, and a 36.2% error reduction compared to the baseline. The above approach improves the accuracy of outdoor localisation; however, it does not work for indoor localisation due to the increase of multiple radio propagation paths. Therefore, our third contribution is an improved super-resolution algorithm for indoor localisation. By exploiting both the original and the conjugate of the physical layer, the algorithm can resolve the multiple paths from multiple reflectors in clustered indoor environments. We evaluate its performance in an indoor area of 25 m × 15 m, which shows that a median error of 2.4 m can be achieved, which is 47.8% and 38.5% less than the baseline approach and the approach without using the conjugate information, respectively. Our evaluation also shows that, different to previous studies in Wi-Fi localisation systems that have significantly wider bandwidth, time-of-fight (ToF) estimation is less effective to LoRa localisation systems with narrowband radio signals