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Long Range (LoRa) is a wireless modulation used to provide longrange connectivity to low-power devices of the Internet of Things (IoT). LoRa gateways use hardware chips called demodulators in order to demodulate concurrent frames on different channels or spreading factors. In this paper, we establish several theoretical results on the performance of fundamental demodulator allocating strategies. In the single gateway scenario, we first prove the optimality of the basic preemptive allocation strategy. Next, in the multi-gateway scenario, the greedy non-collaborative strategy, which is currently implemented in LoRa gateways, is shown to achieve a very large approximation ratio. As an alternative, we demonstrate that a preemptive non-collaborative strategy has an approximation ratio of 2, and furthermore, that a preemptive smartcollaborative strategy reaches an approximation ratio of 3/2, for two gateways. These seminal results imply that the current performance of multi-gateway LoRa deployments can be largely improved by the proposed collaborative demodulator allocation strategies.

International audience; IoT technologies are becoming more pervasive in many critical applications which leads to an increase in the deployment of the popular LoRaWAN (Long Range Wide Area Network) networks. Therefore, it is essential to characterize the network performance and monitor targeted end nodes. In this paper, a passive packet sniffer is proposed that can monitor LoRaWAN at a given geographical location. Using a commercial gateway, a measurement is conducted to passively collect LoRa (Long Range) packets within a duration of one month. From the acquired data, the transmission parameters of the received packets are analyzed. Furthermore, information is extracted from various fields of the frame structure. Then, a Sequence of Contiguous Packets (SCP) is introduced for providing additional packet labeling beyond the Device Address (DevAddr). This original SCP algorithm classifies a stream of packets transmitted by a single end node, based on the similarities between the packets' parameters. The feasibility of the proposed SCP algorithm is confirmed after presenting statistical analysis and the characteristics of estimated SCPs from the real acquired data.

International audience; LoRaWAN networks can involve large numbers of wireless devices relying on batteries to sense the environment and send data to gateways. A critical trade-off for transmission performance (packet delivery ratio) versus energy conservation (and hence, the device lifespan) appears when deciding the transmission parameters, in particular, the Spreading Factor (SF) to be used by each node. In this paper, we use lightweight reinforcement learning techniques, namely multi-armed bandits, for each node to select an appropriate SF, based on preferences regarding that trade-off. Unlike previous works on that topic, we relax some assumptions to aim at a realistic implementation: our solution does not assume immediate rewards, or that each device communicates with only one gateway. Additionally, we build explicit MAC commands for the method to work in practice and implement it in the ns-3 simulator using a state-of-the-art LoRaWAN module. We share the source code of our implementation and our simulation results. Those simulations show that when energy conservation is critical for IoT nodes, such lightweight learning algorithms outperform LoRaWAN's legacy Adaptive Data Rate algorithm, both in single- and multi-gateway scenarios.

International audience; Long Range (LoRa) technology constitutes one of the major enablers of future Internet-of-Things (IoT) applications, such as monitoring of challenged environments and smart buildings. However, crucial issues in the context of multi-gateway LoRa networks have been overlooked. In particular, most existing methods did not consider the stringent constraint of limited number of demodulators at each gateway. Therefore, we devise a gateway selection method for uplink LoRa transmissions, where this limited availability of demodulators is fully considered. We propose an optimization approach based on the auction mechanism, where each IoT device is pre-assigned to a unique gateway, so as to maximize the total amount of demodulated transmissions without redundancy at the network server. Furthermore, a low complexity method is also designed, where devices are partitioned into groups and where auctions are parallelized. Numerical results show that the proposed methods largely outperform benchmark algorithms in terms of the network utility function and sum-rate, while approaching the upper bound performance. The proposed methods are particularly suited to cope with the inherent dynamics of mobile LoRa IoT networks, as highest gains are attained for demodulation latencies in the order of tens to hundreds of milliseconds.

National audience; LR-FHSS (Long-Range Frequency Hopping Spread Spectrum) est une récente modulation conçue pour que des équipements fonctionnant sur piles puissent transmettre des données à des satellites à basse orbite. Pour décoder une trame, la passerelle située sur le satellite doit recevoir au moins une copie de l'entête, et une grande proportion des fragments du payload. Toutefois, les entêtes LR-FHSS, plus longs que les fragments, ont de grandes chances d'être perdus lorsque le nombre de transmissions concurrentes est élevé. Dans ce papier, nous proposons une heuristique pour récupérer de telles trames LR-FHSS qui sont reçues sans entête. Nous montrons par simulation que notre heuristique a un comportement proche de l'optimal, en comparant ses résultats à ceux obtenus via un modèle linéaire en nombre entiers. Nous montrons aussi que notre heuristique peut récupérer beaucoup de trames reçues sans entête, tout en générant peu de faux positifs.

International audience; The ubiquity of mobile devices equipped with radio communication technologies has made large-scale data collection on human mobility commonplace [SSGL15]. Therefore, with the lack of datasets, data collection and publication are raising new scientific questions. In this paper, we present the PILOT dataset and its privacy-preserving data collection methodology for wireless communication technologies. The dataset is a collection of four pieces of information collected together in different mobility contexts. It includes three wireless communication technologies: WiFi beacons, Bluetooth Low Energy (BLE) beacons and Long Range Radio (LoRa) packets, as well as additional information that includes: Acceleration, Roll and Pitch, all collected at the same time. We provide the keys to replicate this data collection. The dataset is collected for about 60 hours, with a size of 150 MB using Pycom's FiPy devices and is uploaded to GitHub. We believe that the combination of the different types of information collected in different mobility scenarios constitutes a new generation of a rich dataset.; L'omniprésence des appareils mobiles équipés de technologies de communication radio a rendu courante la collecte de données à grande échelle sur la mobilité humaine [SSGL15]. Par conséquent, avec le manque d'ensembles de données, la collecte et la publication de données s'avèrent lever de nouvelles questions scientifiques. Dans cet article, nous présentons l'ensemble de données PILOT et sa méthodologie de collecte de données préservant la confidentialité des technologies de communication sans fil. L'ensemble de données est une collection de quatre éléments d'information collectés conjointement dans différents contextes de mobilité. Il comprend trois technologies de communication sans fil : balises WiFi, balises BLE (Bluetooth Low Energy) et paquets LoRa (Long Range Radio), ainsi que des informations supplémentaires qui comprennent : Accélération, Roulis et Tangage, toutes collectées en même temps. Nous fournissons les clés pour reproduire cette collecte de données. Le jeu de données est collecté pendant environ 60 heures, avec une taille de 150 Mo en utilisant les dispositifs FiPy de Pycom et il est téléchargé sur GitHub. Nous pensons que la combinaison des différents types d'informations collectées dans différents scénarios de mobilité constitue une nouvelle génération d'un riche ensemble de données.

International audience; LoRa and LoRaWAN are one of the most common wireless technologies used today in the Internet of Things. If until now LoRa was strictly used in sub-GHz bands, a new version has been released for the 2.4 GHz band that does not have any duty cycle restrictions and that allows the use of higher datarates,which opens the door to the deployment of new applications (such as asset tracking or indoor localization). In this paper,we present the first extensive evaluation of LoRa 2.4 GHz in a typical indoor environment, both in the presence and lack of human and WiFi activities. We run an exhaustive evaluation of all 128 possible combinations of the different LoRa physical parameters (spreading factor, bandwidth and coding rate) and we show that despite the use of higher frequency, LoRa is capable of maintaining a good connectivity throughout the building, similar to what was observed in sub-GHz bands. Still, some configurations were clearly affected by the daily life activities in the building during the working hours of weekdays.

International audience; The Internet of Things faces a significant scaling issue due to the rapid growth of the number of devices and asynchronous communications. Different technologies in the license-free industrial, scientific, and medical (ISM) band have been widely deployed to fill this gap. LoRa and Sigfox are the most common. Many devices can use the ISM band if they obey the regulations and cope with internal and external interference. However, when there is massive connectivity, the effect of the inter and intra-network interference between multiple networks is significant. This study uses a deep learning-based technique to decode signals and deal with the interference in the uplink of a LoRa network. Two classification-based symbol detection methods are proposed using a deep feedforward neural net-work (DFNN) and a convolutional neural network (CNN). The proposed receivers can decode the signals of a selected user when many LoRa users transmit simultaneously using the same spreading factor over the same frequency band (intra-spreading factor interference), and multiple Sigfox users interfere (inter-network interference). Simulation results show that both receivers outperform the conventional LoRa receiver in the presence of interference. For a target symbol error rate (SER) of 10 −3 , the proposed DFNN and CNN-based receivers attain around 2 dB and 3.5 dB gain, respectively.

International audience; There is a lack of studies about the susceptibility of LoRa networks to specific interference sources such as broadband jammers and the train catenary, which produces transient interference in a railway environment. In this paper, we investigate this topic by separately analyzing the proprietary LoRa physical layer and the open medium access control layer. Such an approach allows us to decompose the interference effects into two elements: the signal integrity effects at the physical layer and the counter measures of the LoRaWAN protocol.

International audience; Direct-to-Satellite IoT (DtS-IoT) is a promising approach to deliver data transfer services to IoT devices in remote areas where deploying terrestrial infrastructure is not appealing or feasible. In this context, low-Earth orbit (LEO) satellites can serve as passing-by IoT gateways to which devices can offload buffered data to. However, transmission distances and channel dynamics, combined with highly constrained devices on the ground makes of DtS-IoT a very challenging problem. Here, we present LoRa-based approaches to realize scalable and energy-efficient DtS-IoT. Our study includes the Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) physical layer, currently on the roadmap of future space IoT projects. Specifically, we propose uplink transmission policies that exploit satellite trajectory information. These schemes are framed with a theoretical Mixed Integer Linear Programming (MILP) model providing an upper bound on performance as well as inspiration for scheduled DtS-IoT solutions. Simulation results provide compelling evidence that trajectory based policies can duplicate the amount of IoT nodes, while specific variants can further boost the scalability by 30% without incurring energy penalties. We also quantify that LR-FHSS can improve the deployment scalability by a factor of 75x at the expenses of 30% higher device's power consumption compared to the legacy LoRa modulation.

In Low Power Wide Area (LPWA) networks, radio localization based on Time of Arrival (TOA) measurements collected from gateways synchronized on GPS time is an appealing technology for Internet of Things (IoT). However, it is hard to predict the actual accuracy that could be expected from a given deployment without taking into account the propagation channel complexity. This paper proposes a new approach to generate a localization accuracy map (LAM) based on Cramér-Rao lower bound (CRLB) and 3D buildings models to predict the propagation conditions. A comparison with measurements from LPWA field trials conducted in the city of Grenoble (France) is presented, comprising more than 300 000 LPWA transmissions collected. We show that for an infrastructure composed of 6 LPWA gateways, our LAM is able to predict the performance obtained with an maximum likelihood estimator (MLE) localization algorithm with only 12% of mismatch.

National audience; Les réseaux LoRaWAN font partie des technologies clefs pour la collecte de données dans l'Internet des Objets sur des zones étendues. Le protocole LoRaWAN propose principalement une voie montante pour la remontée des informations issues des capteurs, mais utilise également une voie descendante pour transmettre des commandes de paramétrage ou les acquittements des trames de données quand nécessaire. Dans tous les travaux de la communauté, cette voie descendante est supposée orthogonale à la voie montante, en raison de l'utilisation d'une modulation inversée entre ces deux voies. A l'aide d'expérimentations utilisant des radio-logicielles, nous montrons pour la première fois que cette rumeur disait faux : le taux de livraison de trames peut chuter de 20% lorsque des transmissions concurrentes sur les voies montantes et descendantes se produisent.

International audience; The new emerging technologies enable the appearance of the 5G system and beyond that offers a plethora of services and target new verticals. One of these verticals is the large-scale Internet of Things (IoT) that is expected to be used everywhere in our daily lives. The traffic would likely be increased due to these emerging verticals. To overcome such challenges, network slicing and softwarization will play a crucial role in addressing these requirements and ensuring service level agreements (SLAs). Thus, there is a need to provide efficient and flexible network slice management mechanisms to handle the hurdles that come with the emerging industrial verticals. This paper focuses on network slicing in LoRa networks. We suggest a centralized coalition game-based network slicing strategy to manage LoRa nodes efficiently. According to the Kmeans clustering algorithm, the proposed solution is deployed within clustered players to maximize reliability while ensuring the SLA of the LoRa slices. Simulation results clearly show that our proposed approach improves Packets' Success Rate (PSR), Network Energy Consumption (NEC), and guarantees prioritization between slices.

International audience; Recent advances in wireless communication technologies are having a great impact on people’s life, especially in the field of healthcare industry that provides a remote monitoring enabling medical staff to follow up the patient and diagnose his disease. LoRa wireless technology is becoming one of the most energetic effective solutions for Wireless Body Area Networks (WBANs) communications. In this work, we propose a LoRa-based low power healthcare WBAN platform called HeaLoRa for an adaptive patient monitoring process. Physicians can remotely monitor patient’s temperature, oxygen saturation level, blood pressure and heart rate to prevent any abnormality. Moreover, data acquisition and transmission are controlled based on a power consumption optimization strategy aiming to reduce redundant data. Based on the Early Warning Score (EWS), the system configuration is dynamically adapted, using a Fuzzy logic controller that makes the decision about the system sleep mode duration and the sent data rate. Furthermore, an analytical model of the energy consumption for acknowledged LoRa transmission is presented in this paper. The graphical abstract of the paper illustrates a medical application of a wireless body area network system where LoRa technology is used to transmit the data to a gateway then the data is transmitted to the doctor using IP based technology. By comparing with a reference system, the simulation results indicate that our system consumes 3 to 10 times less of energy depending on the studied scenario.

IoT networks are more and more present nowadays. Some IoT protocols share the same bandwidth leading to interference on neighboring networks and decrease of overall coverage. To contribute to this problem, an analytical study of the coverage of a LoRa network with underlying uncoordinated IoT networks for uplink transmissions is presented in this paper. Using stochastic geometry, closed form analytical expressions are proposed allowing to analyze the success and coverage probabilities for a LoRa network. An appropriate model of the path loss including real-life values is used to characterize the log-distance propagation parameters. The interference comes from both the LoRa network itself and the underlying IoT networks, modeled with an $\alpha $ -stable distribution based on recent measurements. It is shown that for an environment with a huge amount of surrounding uncoordinated IoT networks, the gateways deployment should be doubled to reach a decent coverage probability, compared to an environment where the underlying interfering networks are not considered.

National audience; Le nouveau paradigme de communication, Direct-to-Satellite-IoT (DtS-IoT), est une approche très prometteuse pour le transfert de données depuis/vers des appareils IoT dans des zones reculées où le déploiement d'une infrastructure terrestre n'est pas faisable. Dans ce contexte, les satellites en orbite terrestre basse (LEO) peuvent équiper des passerelles IoT comme celles de LoRa, pour faciliter la collecte de données des capteurs situés sur Terre en ligne de vue directe. Cependant, cette communication est soumise à plusieurs défis : grandes distances de transmission (500 à 2000 km), couverture sporadique et de courte durée (environ 7 minutes), liaisons inter-satellites à faible bande passante, et appareils IoT contraints en énergie. Pour permettre à la communauté de mettre en oeuvre et d'étudier des protocoles pour la communication DtS-IoT de façon réaliste, nous proposons un nouvel outil de simulation à événements discrets : FLoRaSat. Le simulateur s'appuie sur Omnet++ et implemente un scénario de communication DtS-IoT de de bout en bout comprenant 16 satellites LEO interconnectés et 1500 noeuds IoT sur Terre qui communiquent à l'aide du protocole LoRaWAN.

International audience; In the Internet of Things (IoT) context such as Low Power Wide Area Network (LPWAN), it is essential to reduce the packet losses, e.g., to save energy. Decentralized artificial intelligence techniques have been proposed to combat radio collisions, but the approach here is extended to deal additionally with the channel propagation effects. In this article, a Quality of Channel Allocation (QoC-A) learning technique based on bandit algorithms is proposed in order to choose the transmission channel. This aims to reduce the effect of the propagation impairments between the radio channels while using the Effective Signal Power (ESP) as a quality metric. In addition, a Discounted QoC-A (DQoC-A) algorithm is proposed to adapt rapidly to any abrupt change in the channelsand#x2019; conditions. An experimental campaign on a real IoT device is carried out to demonstrate the low complexity and efficiency of these proposed decentralized algorithms. In the given results, QoC-A outperforms the classical UCB policy with a more accelerated learning process. On the other hand, the feasibility of using the DQoC-A in non-stationary scenarios is illustrated by its rapid convergence when abrupt changes in the channelsand#x2019; conditions occur. At the end of the process, these proposed learning techniques give 4.1 and 2.4 times fewer packet losses than the traditional ones with a random channel assignment scheme, in the stationary and non-stationary scenarios, respectively.

International audience; One major goal of Beyond 5G and 6G networks is to provide connectivity for a massive number of Internet-of-Things (IoT) devices. Towards that goal, Long Range (LoRa) is a promising physical layer technology which features low data-rates and large communication ranges, while requiring only low power. However, as the number of devices increases, more and more collisions occur, hence severely degrading LoRa system performances. To cope with this critical drawback, several LoRa collision decoding algorithms and MAC protocols have been proposed. The purpose of this article is to present how collision decoding algorithms interact with MAC layer protocols, and to discuss the potential of such integrated approaches. To do so, we first classify the collision decoding algorithms according to their principles and distinctive features, and compare some reference algorithms in a single simulation setup, using a Software Defined Radio (SDR) hardware. Then, we analyze how each class of MAC protocols can benefit from each category of collision decoding algorithms. Finally, we discuss longterm perspectives and open issues in this active research area.

International audience; The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially LoRaWAN. In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated with each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems to get access to a wider band.

International audience; The response of several Long-range (LoRa) wireless devices to total ionizing dose has been assessed using $^{60}$Co gamma-rays. We found that the radiation tolerance of the different tested devices is comprised between 220 and 1600 Gy.

International audience; This paper presents an embedded device based on the Semtech SX1280 IC, which supports LoRa technology at 2.4GHz. The system is integrated into a circularly polarized (CP) antenna with 30 mm in diameter and 8.2 mm in height. The proposal hardware is measured and compared to the actual Ebyte E28 module that using the linear polarized (LP) antenna as a printed monopole.

International audience; This paper presents the deployment of a Low Power Wide Area Network (LPWAN) in Danang city. The different steps from the preliminary test to the full network deployment are reported. Interference issues with mobile phone network is also discussed. The different method and materialused to assess network performances are also reported.

International audience; LoRa is one of the leading technologies for Low-Power Wide Area Networks and the Internet of Things. Collisions in LoRa might cause retransmissions, which negatively impact the network performance and scalability. Several algorithms have been proposed to decode colliding frames under specific conditions. However, there remain indistinguishable frames due to uncertainties in some or all symbols. In this paper, we propose a general algorithm that significantly improves the recovery capabilities of existing algorithms by leveraging the LoRa coding techniques. Simulation results show that our algorithm can significantly reduce the number of the failed decoding of LoRa frames and improve the performance of the network.

International audience; The increasing number of devices together with uncoordinated transmissions result in a major challenge of scalability in the Internet of things. This paper deals with signal detection in the uplink of a LoRa network through a deep learning-based approach. Two strategies are proposed: regression for bit detection based on a deep feedforward neural network and classification for symbol detection based on a convolutional neural network. These receivers can decode a selected user's signals when multiple users simultaneously transmit over the same frequency band with the same spreading factor. Simulation results show that both receivers outperform the classical LoRa one in the presence of interference. The results show that the introduced approach is relevant to deal with the scalability issue.

International audience; This paper examines the effect of Band Jamming (BJ) and Tone Jamming (TJ) on LoRa signals in a flat Additive White Gaussian Noise (AWGN) channel. In this scenario, LoRa proves to have good resiliency against these jamming attacks. Furthermore, a simple and lightweight BJ and TJ jammer detection scheme is derived. Theoretical and simulation results shows good detection capability, especially with Single Tone Jamming (STJ).

International audience; IoT networks have been omnipresent in urban and sub-urban areas since a few years ago. Even if all the IoT protocols do not use the same characteristics (modulation, resource sharing, transmit power, bandwidth), sometimes they share the same bands, which can inevitably lead to interference on the neighboring networks, and thus to a decrease in the overall coverage. In this paper, we present an analytical study of thecoverage for a LoRa network with underlying uncoordinated IoT networks. Thanks to stochastic geometry, we propose closed form expressions and analyze the success and the coverage probabilities for a LoRa network in an infinite area. The interference taken into account in this work come from both the LoRa network itself (so called co-SF interference) and the underlying IoT network, modeled with an alpha-stable distribution,which parameters are based on recent measured values.

International audience; This paper deals with a general and complete analysis of the frame error rate in LoRa system, not only considering the payload error rate, but also the sync word (carrying network information) and the header (carrying control information) error rates. It is proved that, in the high signal-to-noise ratio (SNR) range, it is more likely to reject a LoRa frame due to an erroneous sync word estimation rather than an erroneous header or payload decoding, due to the fact that it is not coded. The theoretical results are then verified through simulations.

International audience; This work presents an instruction-set extension to the open-source RISC-V ISA (RV32IM) dedicated to ultra-low power (ULP) software-defined wireless IoT transceivers. The custom instructions are tailored to the needs of 8/16/32-bit integer complex arithmetic typically required by quadrature modulations. The proposed extension occupies only 2 major opcodes and most instructions are designed to come at a near-zero energy cost. Both an instruction accurate (IA) and a cycle accurate (CA) model of the new architecture are used to evaluate six IoT baseband processing test benches including FSK demodulation and LoRa preamble detection. Simulation results show cycle count improvements from 19% to 68%. Post synthesis simulations for a target 22nm FD-SOI technology show less than 1% power and 28% area overheads, respectively, relative to a baseline RV32IM design. Power simulations show a peak power consumption of 380 µW for Bluetooth LE demodulation and 225 µW for LoRa preamble detection (BW = 500 kHz, SF = 11).

In this thesis, we focus on radio resource planning issues for low power wide area networks based on NB-IoT and LoRa technologies. In both cases, the average behavior of the network is considered by assuming the sensors and the collectors are distributed according to independent random Poisson Point Process marked by the channel randomness. For the NB-IoT, we elaborate a statistical dimensioning model that estimates the number of radio resources in the network depending on the tolerated delay access, the density of active nodes, the collectors, and the antenna configuration with single and multi-user transmission. For the LoRa network, we propose a multi-sub band allocation technique to mitigate the high level of interference induced by nodes that transmit with the same spreading factor. To dynamically allocate the spreading factor and the power, we present a Q-learning multi-agent approach to improve the energy efficiency., Cette thèse étudie le problème de planification des ressources pour les réseaux IoT longues portées basés sur les technologies NB-IoT et LoRa. Dans les deux cas, on suppose que les capteurs et les collecteurs sont distribués suivant des processus de points de Poisson spatial indépendants marqués par le caractère aléatoire du canal. Pour le NB-IoT, nous élaborons un modèle de dimensionnement statistique qui estime le nombre de ressources radio nécessaires en fonction du délai d’accès toléré, de la densité des nœuds actifs, des collecteurs et de la configuration de l’antenne. Pour le réseau LoRa, nous proposons une technique d’allocation de plusieurs sous-bandes pour atténuer le niveau élevé d’interférence induit par les nœuds qui transmettent avec le même facteur d’étalement. Pour allouer dynamiquement le facteur d’étalement et la puissance, nous présentons une approche d’apprentissage automatique avec multi-agents qui permet d’améliorer l’efficacité énergétique.

International audience; In this paper we present a complete GNU Radio, dynamic and customizable physical (PHY) layer for long range (LoRa) transceiver, usable with the FIT/CorteXlab radio testbed and derived from the original EPFL LoRa implementation. The created adaptation, through a standardized interface, allows end-users an easy connection to an external medium access control (MAC)/upper layer to experiment scenarios in a fully reproducible and isolated environment. It also provides several PHY layer key performance indicators and metrics such as signal to noise ratio (SNR), received signal energy, binary error rate (BER) and other, that can be used to gauge the performance of the ongoing communications as well as construct MAC layers able to use this information. Finally, the interface allows our plug&play PHY solution to be used with any existing or newly adapted MAC layer, without having to implement it in GNU Radio. This will be demonstrated during our presentation.

International audience; A novel multi-technology indoor positioning system, Poucet, designed for military and firefighter operations, is introduced in this paper. A mobile agent, wearing a lightweight tracker, is located in real-time during indoor operations through a combination of outdoor stations and indoor beacons dropped by the agent on his way. Beacons and trackers integrate multiple radio positioning technologies, including Global Positioning System, (Long range Radio (LoRa 868MHz and 2.4 GHz), Ultrawide-band (UWB), and altimeters. Poucet's distributed architecture is presented along with the main features of each of the technologies used. A multi-input fusion algorithm provides continuous and reliable positioning. We report experimental results obtained during benchmarks scenarios conducted by the French National Defense on the presented prototypes.

© 2020 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 works. The Internet Engineering Task Force (IETF) Low Power Wide Area Network (LPWAN) Working Group has developed the Static Context Header Compression (SCHC) framework to enable IPv6 over LPWAN. In order to support 1280-byte packets, as required for IPv6, SCHC includes a fragmentation functionality, since relevant LPWAN technologies offer very short data unit sizes and do not provide native fragmentation mechanisms. SCHC offers 3 fragmentation modes: No-ACK, ACK-Always, and ACK-on-Error, the latter being especially promising due to its reliability and high efficiency. In this article, we develop a mathematical model to compute the most critical performance parameters for the SCHC ACK-on-Error mode, namely, the acknowledgment traffic incurred by a fragment receiver for the successful delivery of a fragmented packet. The model is used to evaluate the SCHC ACK-on-Error mode performance, as well as to optimally tune its main parameters when used over LoRaWAN and Sigfox, for different packet sizes. Additionally, we illustrate how our derived optimal settings allow to reduce the acknowledgment traffic in a number of scenarios.

In this paper, we aim to enhance the spectral efficiency of Chirp Spread Spectrum (CSS) communications by transmitting simultaneously and on the same bandwidth several non orthogonal signals. Each receiver is able to demodulate its information taking advantage of a controlled time desynchronization between transmitted signals and/or an amplification diversity coupled with a successive interference cancellation algorithm. Various simulation results demonstrate the relevance of our proposition to decode multiple superposed CSS signals in a downlink situation.

International audience; Received Signal Strength Indicator (RSSI)-based fingerprinting is currently viewed as an important technique for the positioning capabilities in the Internet of Things (IoT). However, in the case of practical measurement, the localization methods based on RSSI are easily affected by the temporal and spatial variation, which contributes to most of the estimation errors in current systems. In this paper, the feasibility of utilizing the Channel State Information (CSI) for localization is studied, after knowing that the CSI contains information about the channel between the sender and receiver at the level of individual data subcarriers. Unlike most of the previous work, the intended approach is to use the entire subcarrier magnitudes without averaging or any reduction of the obtained narrowband CSI. Moreover, the frequency hopping in the LoRa systems should be a profit for localization by getting access to a wider band. In order to obtain a reliable basis for this approach, an outdoor measurement campaign is performed in the area of the Campus Beaulieu in Rennes to estimate the CSI of transmitted LoRa signals from different locations. For this, it is necessary for the individual channels from each different position to be appropriately different from one another to achieve significant localization gain. Hence, a comparison is done investigating the attainable evolution in the CSI at each location based on the CSI slope versus its average amplitude. In the given results, the feasibility of using the proposed technique is asserted by the drastic stability of the CSI slope over time and space, in contrary to the CSI average amplitude. This manifests the robustness of the CSI to the signal fluctuations and its more valuable rendering than the RSSI.

International audience; Internet of Things (IoT) technology has become ubiquitous in a multitude of applications and its use is growing. However, the expansion of IoT faces a major difficulty: scalability, that is, very dense deployment of communicating devices is currently limited. In long-range networks, such as LoRa, the downlink is critical because it limits the number of acknowledgements that can be sent, and consequently reliability. It also limits the possibility to update the devices, which could be critical when they are deployed for decades. To overcome those problems, we propose a solution, inspired by Non Orthogonal Multiple Access (NOMA) techniques, to increase by at least one order of magnitude the number of devices that can be addressed. While the approach differentiates the devices by the power allocated to them, it differs from the vast majority of previous works on power domain NOMA because it does not require interference cancellation. Instead, it benefits from the spectrum spreading of the modulation scheme (chirp spread spectrum), where, at the end of the decoding phase, the information carried by a symbol is found in the position of a peak in the Fourier domain. In the vast majority of cases, the information from different users results in different peak positions, not creating any interference. In that sense, we get closer to avoidance schemes such as time or frequency hopping, but without using a code. In this article, we propose a new solution for NOMA in the power domain that does not suffer from the limitations induced by interference cancellation residues. The proposed system, including preamble detection and channel estimation, is presented and evaluated by simulations. We demonstrate that our proposed scheme increases the number of devices by one order of magnitude compared to the current system which allows addressing only one user at a time and maintains full compatibility with the LoRa physical layer standard. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

The connection of many electronic devices is based on ambient, energy-efficient and long range wireless networks. The technical and economic model of cellular networks can serve as a basis, but the many use cases require breaking this technological monopoly and thinking of the networks of tomorrow as interoperable and multi-technology.Emerging LPWAN networks are a compromise between energy consuming cellular networks and wireless sensor networks which have a reduced radio range. This new paradigm opens up new fields of research by making it possible to hybridize local networks and cellular networks. This thesis deals with the interoperability of these networks under different architectural aspects. The major contribution of this thesis lies in the deployment of a metropolitan LoRa network in the city of Toulouse allowing researchers to create and evaluate new protocols in real conditions for the city of tomorrow.; La connexion de nombreux éléments électroniques se base sur des réseaux sans fil ambiants, économes en énergie et longue distance. Le modèle technique et économique des réseaux cellulaires peut servir de base mais les nombreux cas d'usages nécessitent de casser ce monopole technologique et de penser les réseaux de demain comme interopérables et multi-technologies. Les réseaux LPWAN émergents sont un compromis entre les réseaux cellulaires consommateurs en énergie et les réseaux de capteurs qui ont une portée réduite. Ce nouveau paradigme ouvre de nouveaux champs de recherche en permettant d'hybrider les réseaux locaux et les réseaux cellulaires. Cette thèse traite de l'interopérabilité de ces réseaux sous différents aspects architecturaux. La contribution majeure de cette thèse réside dans le déploiement d'un réseau LoRa métropolitain sur la ville de Toulouse permettant aux chercheurs de créer et d'évaluer de nouveaux protocoles en conditions réelles pour la ville de demain.

The connection of many electronic devices is based on ambient, energy-efficient and long range wireless networks. The technical and economic model of cellular networks can serve as a basis, but the many use cases require breaking this technological monopoly and thinking of the networks of tomorrow as interoperable and multi-technology.Emerging LPWAN networks are a compromise between energy consuming cellular networks and wireless sensor networks which have a reduced radio range. This new paradigm opens up new fields of research by making it possible to hybridize local networks and cellular networks. This thesis deals with the interoperability of these networks under different architectural aspects. The major contribution of this thesis lies in the deployment of a metropolitan LoRa network in the city of Toulouse allowing researchers to create and evaluate new protocols in real conditions for the city of tomorrow., La connexion de nombreux éléments électroniques se base sur des réseaux sans fil ambiants, économes en énergie et longue distance. Le modèle technique et économique des réseaux cellulaires peut servir de base mais les nombreux cas d'usages nécessitent de casser ce monopole technologique et de penser les réseaux de demain comme interopérables et multi-technologies. Les réseaux LPWAN émergents sont un compromis entre les réseaux cellulaires consommateurs en énergie et les réseaux de capteurs qui ont une portée réduite. Ce nouveau paradigme ouvre de nouveaux champs de recherche en permettant d'hybrider les réseaux locaux et les réseaux cellulaires. Cette thèse traite de l'interopérabilité de ces réseaux sous différents aspects architecturaux. La contribution majeure de cette thèse réside dans le déploiement d'un réseau LoRa métropolitain sur la ville de Toulouse permettant aux chercheurs de créer et d'évaluer de nouveaux protocoles en conditions réelles pour la ville de demain.

The connection of many electronic devices is based on ambient, energy-efficient and long range wireless networks. The technical and economic model of cellular networks can serve as a basis, but the many use cases require breaking this technological monopoly and thinking of the networks of tomorrow as interoperable and multi-technology. Emerging LPWAN networks are a compromise between energy consuming cellular networks and wireless sensor networks which have a reduced radio range. This new paradigm opens up new fields of research by making it possible to hybridize local networks and cellular networks. This thesis deals with the interoperability of these networks under different architectural aspects. The major contribution of this thesis lies in the deployment of a metropolitan LoRa network in the city of Toulouse allowing researchers to create and evaluate new protocols in real conditions for the city of tomorrow., La connexion de nombreux éléments électroniques se base sur des réseaux sans fil ambiants, économes en énergie et longue distance. Le modèle technique et économique des réseaux cellulaires peut servir de base mais les nombreux cas d'usages nécessitent de casser ce monopole technologique et de penser les réseaux de demain comme interopérables et multi-technologies. Les réseaux LPWAN émergents sont un compromis entre les réseaux cellulaires consommateurs en énergie et les réseaux de capteurs qui ont une portée réduite. Ce nouveau paradigme ouvre de nouveaux champs de recherche en permettant d'hybrider les réseaux locaux et les réseaux cellulaires. Cette thèse traite de l'interopérabilité de ces réseaux sous différents aspects architecturaux. La contribution majeure de cette thèse réside dans le déploiement d'un réseau LoRa métropolitain sur la ville de Toulouse permettant aux chercheurs de créer et d'évaluer de nouveaux protocoles en conditions réelles pour la ville de demain.

International audience; Les objets connectés utilisant la norme LoRaWAN peuvent réduire leur consommation d'énergie en quittant leurétat de veille uniquement pour envoyer leurs données. Cependant, cette technique induit une latence forte de la liaison descendante qui n'est pas compatible avec les applications contraintes en latence comme le contrôleà distance ou celles utilisant des actuateurs. Afin de surmonter ce compromis entre la consommation d'énergie et la latence, nous proposons dans cet article un protocole MAC exploitant une architecture de réseau hétérogène composée de radio longue portée LoRaWAN et de radio courte portée utilisant la wake-up radioà très faible consommation. Grâceà cette nouvelle architecture de réseau et au protocole MAC approprié, la latence peutêtre réduite tout en maintenant ou même en augmentant l'efficacitéénergétique. Pour un cluster composé de dix noeuds, des gains simultanés de 3.33 et de 2.11 peuventêtre obtenus respectivement en latence et en consommation d'énergie.

In this dissertation, we consider performance aspects of LoRa, one of the promisingtechnologies for lightweight smart sensors for the Internet of Things (IoT). LoRa belongs to a new class of Low Power Wide Area (LPWA) networks and defines a specificradio layer based on the Chirp Spread Spectrum modulation and a simple MediumAccess Control called LoRaWAN. The operation of LoRaWAN is similar to ALOHA: adevice wakes up and sends a packet to a Gateway right away. This choice of the accessmethod highly impacts the capacity of LoRa and its scalability to a large number ofdevices. It results in a high level of packet losses due to collisions as the number ofdevices increases.Motivated by these challenges, we have designed and implemented enhanced access methods to improve LoRa performance. First, we have taken advantage of CarrierSense Multiple Access (CSMA) to lower the collision ratio. We have used the NS-3 simulator to evaluate the scheme and the simulation results show that CSMA considerablylowers the collision ratio while only slightly increasing energy consumption. Second, wehave proposed Timemaps, a new access method for improving the performance of LoRa.The idea is to build a temporal map of all transmissions of IoT devices by a Gatewayand distribute the schedule during join. Schedules admit overlapping transmissions ofdifferent spreading factors and as devices usually allocate a spreading factor in functionof the increasing distance from the Gateway, transmissions will be in fact orthogonal,which leads to increased overall capacity of the network.We have used the NS-3 simulator to evaluate Timemaps in both cases of perfect clocks and clocks with a drift.The simulation takes into account quasi-orthogonality of transmissions with differentspreading factors and the capture effect. The results show that Timemaps benefitsfrom remarkably higher packet delivery ratio and considerably lower the collision ratiocompared to LoRaWAN along with moderately increased energy consumption.To validate both schemes we have developed an NS-3 module that simulates thefine-grain LoRa operation. The module uses an energy framework implemented in NS-3to estimate energy consumption at battery powered nodes and in the whole network.; Dans cette thèse, nous explorons des aspects performances de LoRa, l’une des technologies prometteuses pour des équipments IoT. LoRa appartient à une nouvelle classede réseaux appelés “Low Power Wide Area Networks” (LPWAN) et définit une couchede radio spécifique basée sur la modulation “Chirp Spread Spectrum” et une méthodesimple d’accès appelée LoRaWAN. Le fonctionnement de LoRaWAN est similaire àALOHA: un appareil se réveille et envoie immédiatement un paquet à une passerelle.Ce choix de la méthode d’accès a un impact important sur la capacité de LoRa et sonévolutivité vers un grand nombre d’appareils. Il en résulte un niveau élevé de paquetsperdus suite aux collisions à mesure que le nombre d’appareils augmente.Motivés par ces défis, nous avons conçu et mis en œuvre deux méthodes d’accèsaméliorées pour LoRa. Tout d’abord, nous avons proposé d’appliquer la technique“Carrier Sense Multiple Access” (CSMA) à LoRa pour diminuer le nombre de collisions. Nous avons utilisé le simulateur NS-3 pour évaluer le schéma et les résultatsde la simulation montrent que CSMA réduit considérablement le taux de collisionstout en n’augmentant que légèrement la consommation d’énergie. Ensuite, nous avonsproposé Timemaps, une nouvelle méthode d’accès pour améliorer les performances deLoRa. L’idée est de construire une carte temporelle de toutes les transmissions dans lapasserelle et distribuer le planning de transmission lors de l’opération d’attachementd’un équipement au réseau. La carte temporelle permet un chevauchement des transmissions effectués avec des facteurs d’étalement différents. Comme des appareils allouent un facteur d’étalement en fonction de l’éloignement croissant de la passerelle,les transmissions deviennent orthogonales, ce qui conduit à une augmentation globalede la capacité du réseau.Nous avons utilisé le simulateur NS-3 pour évaluer la méthode de Timemaps dansdeux cas: des horloges parfaites et des horloges avec une dérive. La simulation prend encompte la quasi-orthogonalité des transmissions avec différents facteurs d’étalement etl’effet de capture. Les résultats montrent que Timemaps bénéficie d’un taux de livraison de paquets remarquablement plus élevé et du taux de collisions considérablementplus faible par rapport à LoRaWAN avec une consommation d’énergie modérémentaugmentée.Pour valider les deux schémas proposés, nous avons développé un module NS-3qui simule l’opération de LoRa à grain fin. Le module utilise un cadre énergétiqueimplémenté dans NS-3 pour estimer la consommation d’énergie par nœuds et dansl’ensemble du réseau.

In this dissertation, we consider performance aspects of LoRa, one of the promisingtechnologies for lightweight smart sensors for the Internet of Things (IoT). LoRa belongs to a new class of Low Power Wide Area (LPWA) networks and defines a specificradio layer based on the Chirp Spread Spectrum modulation and a simple MediumAccess Control called LoRaWAN. The operation of LoRaWAN is similar to ALOHA: adevice wakes up and sends a packet to a Gateway right away. This choice of the accessmethod highly impacts the capacity of LoRa and its scalability to a large number ofdevices. It results in a high level of packet losses due to collisions as the number ofdevices increases.Motivated by these challenges, we have designed and implemented enhanced access methods to improve LoRa performance. First, we have taken advantage of CarrierSense Multiple Access (CSMA) to lower the collision ratio. We have used the NS-3 simulator to evaluate the scheme and the simulation results show that CSMA considerablylowers the collision ratio while only slightly increasing energy consumption. Second, wehave proposed Timemaps, a new access method for improving the performance of LoRa.The idea is to build a temporal map of all transmissions of IoT devices by a Gatewayand distribute the schedule during join. Schedules admit overlapping transmissions ofdifferent spreading factors and as devices usually allocate a spreading factor in functionof the increasing distance from the Gateway, transmissions will be in fact orthogonal,which leads to increased overall capacity of the network.We have used the NS-3 simulator to evaluate Timemaps in both cases of perfect clocks and clocks with a drift.The simulation takes into account quasi-orthogonality of transmissions with differentspreading factors and the capture effect. The results show that Timemaps benefitsfrom remarkably higher packet delivery ratio and considerably lower the collision ratiocompared to LoRaWAN along with moderately increased energy consumption.To validate both schemes we have developed an NS-3 module that simulates thefine-grain LoRa operation. The module uses an energy framework implemented in NS-3to estimate energy consumption at battery powered nodes and in the whole network.; Dans cette thèse, nous explorons des aspects performances de LoRa, l’une des technologies prometteuses pour des équipments IoT. LoRa appartient à une nouvelle classede réseaux appelés “Low Power Wide Area Networks” (LPWAN) et définit une couchede radio spécifique basée sur la modulation “Chirp Spread Spectrum” et une méthodesimple d’accès appelée LoRaWAN. Le fonctionnement de LoRaWAN est similaire àALOHA: un appareil se réveille et envoie immédiatement un paquet à une passerelle.Ce choix de la méthode d’accès a un impact important sur la capacité de LoRa et sonévolutivité vers un grand nombre d’appareils. Il en résulte un niveau élevé de paquetsperdus suite aux collisions à mesure que le nombre d’appareils augmente.Motivés par ces défis, nous avons conçu et mis en œuvre deux méthodes d’accèsaméliorées pour LoRa. Tout d’abord, nous avons proposé d’appliquer la technique“Carrier Sense Multiple Access” (CSMA) à LoRa pour diminuer le nombre de collisions. Nous avons utilisé le simulateur NS-3 pour évaluer le schéma et les résultatsde la simulation montrent que CSMA réduit considérablement le taux de collisionstout en n’augmentant que légèrement la consommation d’énergie. Ensuite, nous avonsproposé Timemaps, une nouvelle méthode d’accès pour améliorer les performances deLoRa. L’idée est de construire une carte temporelle de toutes les transmissions dans lapasserelle et distribuer le planning de transmission lors de l’opération d’attachementd’un équipement au réseau. La carte temporelle permet un chevauchement des transmissions effectués avec des facteurs d’étalement différents. Comme des appareils allouent un facteur d’étalement en fonction de l’éloignement croissant de la passerelle,les transmissions deviennent orthogonales, ce qui conduit à une augmentation globalede la capacité du réseau.Nous avons utilisé le simulateur NS-3 pour évaluer la méthode de Timemaps dansdeux cas: des horloges parfaites et des horloges avec une dérive. La simulation prend encompte la quasi-orthogonalité des transmissions avec différents facteurs d’étalement etl’effet de capture. Les résultats montrent que Timemaps bénéficie d’un taux de livraison de paquets remarquablement plus élevé et du taux de collisions considérablementplus faible par rapport à LoRaWAN avec une consommation d’énergie modérémentaugmentée.Pour valider les deux schémas proposés, nous avons développé un module NS-3qui simule l’opération de LoRa à grain fin. Le module utilise un cadre énergétiqueimplémenté dans NS-3 pour estimer la consommation d’énergie par nœuds et dansl’ensemble du réseau.

oral; International audience; Low Power Wide Area Network, such as LoRa is one of the main building blocks of the Internet of Things. One of the main issues is to scale up the number of devices and one strong limitation comes from the downlink communication. In fact, the access point is constrained by the duty cycle, therefore it cannot address a large number of devices. We propose a superposition scheme to transmit multiple packets to multiple devices in the same frequency, time slot, and spreading factor. This scheme is applied to the specific physical layer proposed by LoRa, based on the chirp spread spectrum. Our proposal includes the power allocation scheme and the decoding technique that are very specific to this physical layer and show a significant performance improvement, increasing the number of devices that can be connected at least by ten compared to the classical LoRa-like system.

Vu le développement rapide des systèmes E-santé et de la ville intelligente, la nécessité de prendre en charge les capteurs et les actionneurs, pour une automatisation efficace, s'avère être une exigence essentielle pour la maintenance de la communication machine à machine (M2M). Les éléments clés d’un système E-santé performant sont la consommation d’énergie et l’interopérabilité. C’est dans ce contexte que l’on pourrait définir notre thèse,un système dédié aux personnes âgées,agissant et surveillant à l’aide de leur canne connectée qui est mis en œuvre. Notre système consiste en un nœud émetteur positionné sur la canne qui transmet les données relatives aux déplacements et à l'état des personnes âgées à une station de base via la technologie LoRa. Cette dernière utilise ensuite le protocole MQTT (Message Queuing Telemetry Transport) pour interagir avec l'environnement quand une chute est survenue. Plusieurs expériences ont été menées pour évaluer la zone couverte par notre réseau LoRa et la consommation d’énergie de notre système.Les résultats indiquent que la superficie moyenne couverte est d'environ 6 km2 et que la consommation électrique de notre système est au moins dix fois inférieure à celle d'un système de transmission basé sur le GSM, With the increasing surge of M-Health and smart city systems, the need to accommodate sensors and actuators, for an effective automation to take place, proves to constitute a critical requirement for Machine-to-Machine (M2M) communication to be maintained. The key elements for a successful M-Health system are power consumption and maintaining interoperability .It is in this context that the present work could be set, whereby a system dedicated to the elderly tacking and monitoring using their connected walking stick is implemented. Our system consists of a transmitter node positioned on the cane that transmits data related to the position and the state of the elderly, to a base station via LoRa technology, then the latter uses Message Queuing Telemetry Transport (MQTT) protocol to interact with the environment when a fall has occurred. Several experiments have been conducted to evaluate the area covered by our LoRa network and the power consumption of our system. The results indicate that the average covered area is around 6 km2 and the power consumption of our system is at least ten times lower than for a GPRS-based transmission system

In this thesis, we present a multilevel scheme consisting of both hardware and software solutions to improve the daily operational life of firefighters. As a core part of this scheme, we design and develop a smart system of wearable IoT devices used for state assessment and localization of firefighters during interventions. To ensure a maximum lifetime for this system, we propose multiple data-driven energy management techniques for resource constraint IoT devices. The first one is an algorithm that reduces the amount of data transmitted between the sensor and the destination (Sink). This latter exploits the temporal correlation of collected sensor measurements to build a simple yet robust model that can forecast future observations. Then, we coupled this approach with a mechanism that can identify lost packets, force synchronization, and reconstruct missing data. Furthermore, knowing that the sensing activity does also require a significant amount of energy, we extended the previous algorithm and added an additional adaptive sampling layer. Finally, we also proposed a decentralized data reduction approach for cluster-based sensor networks. All the previous algorithms have been tested and validated in terms of energy efficiency using custom-built simulators and through implementation on real sensor devices. The results were promising as we were able to demonstrate that our proposals can significantly improve the lifetime of the network. The last part of this thesis focusses on building data-centric decision-making tools to improve the efficiency of interventions. Since sensor data clustering is an important pre-processing phase and a stepstone towards knowledge extraction, we review recent clustering techniques for massive data management in IoT and compared them using real data for a gas leak detection sensor network. Furthermore, with our hands on a large dataset containing information on 200,000 interventions that happened during a period of 6 years in the region of Doubs, France. We study the possibility of using Machine Learning to predict the number of future interventions and help firefighters better manage their mobile resources according to the frequency of events.; L’objectif de cette de thèse est d’étudier à la fois des solutions matérielles et logicielles pour améliorer les conditions de travail des sapeurs-pompiers. Il s’agit de développer un système intelligent basé sur l’internet des objets pour surveiller l'état de santé des pompiers et aider à les localiser lors des interventions. Dans la première partie de la thèse, nous avons étudié et proposé plusieurs approches permettant de réduire la consommation d’énergie du système afin de maximiser sa durée de vie. La première approche présente un modèle de prédiction basé sur la corrélation temporelle entre les mesures collectées par le même capteur. Il permet de réduire la quantité de données collectées et transmises au centre de contrôle. Ce modèle est exécuté à la fois par le capteur et le centre et qui s'auto-adapte en fonction de l’écart constaté entre les mesures réelles collectées et les mesures prédites. Une deuxième version de cette approche a été étudiée pour prendre en considération la perte de message et la synchronisation entre le capteur et le centre de contrôle. D’un autre côté et pour réduire davantage la consommation d’énergie, nous avons couplé l’approche de prédiction avec un algorithme de collecte de données adaptatif permettant de réduire l’activité du capteur et le taux d’échantillonnage. Toutes ces approches ont été testées via des simulations et de l’implémentation réelle. Les résultats obtenus montrent l’efficacité de ces approches en termes de réduction de la consommation d’énergie tout en gardant l’intégrité de données. La deuxième partie de cette thèse est dédiée au traitement des données issues des interventions des sapeurs-pompiers. Nous avons étudié plusieurs méthodes de clustérisation permettant un prétraitement de données avant l’extraction des connaissances. D’un autre côté, nous avons appliqué des méthodes d'apprentissage profond sur un grand ensemble de données concernant 200.000 interventions qui ont eu lieu pendant une période de 6 ans dans le département du Doubs, en France. Le but de cette partie était de prédire le nombre d’interventions futures en fonction de variables explicatives externes, pour aider les pompiers à bien gérer leurs ressources.

International audience; We consider the technique of carrier sensing for application in a LoRa mesh network aimed at wildlife monitoring. A key challenge in this application is to limit collisions in order to increase the channel capacity. Since CSMA is very rarely applied in LoRa-based networks, our goal is to determine its practical viability. We evaluate the LoRa Channel Activity Detection (CAD) mechanism under laboratory and field conditions. Our results show that both preamble and payload symbols are detectable even at distances exceeding 4 km. Detecting LoRa preamble symbols had a SNR advantage of between 1 and 2 dB over payload symbols. Furthermore, we find that by taking at least 8 consecutive CAD measurements, a clear channel assessment (CCA) comparable to the LoRa frame reception rate can be achieved between two nodes.

Today's Wireless Sensors Networks (WSNs) are becoming more mobile and are often deployed in harsh environments. These networks must be autonomous with light maintenance and having an optimized lifetime. Moreover, these networks suffer from interferences between these different technologies (cross) or within the same technology (mutual).The aim of this thesis is to ensure wireless communications the Internet of Things (IoT) with high reliability, energy-efficiency and robustness to interferences by efficiently exploiting the characteristics of last generation transceivers within a communication protocol stack.During this thesis, we propose to study channel and interference aware communication protocols for both self-deployment of WSNs in restrictive and constrained environment and energy efficient optimization.We will focus on a static approach in the context of the network deployment automation in restrictive and constrained environments. The protocol will detect, characterize and adapt to channel conditions to optimize the link budget of each link and then diagnostic the deployment.; Aujourd’hui, les réseaux sans fils sont de plus en plus mobiles et sont déployés dans des environnements souvent très contraignants. Ces réseaux doivent être autonomes avec peu de maintenance et avoir une durée de vie optimisée. De plus, ces réseaux souffrent d’interférence entre les différentes technologies (cross) ou au sein de la même technologie (mutual). L’objectif de cette thèse est de garantir des communications sans fils pour l’internet des Objets (IoT) ultra-fiables, efficaces énergétiquement et robustes aux interférences en exploitant efficacement les caractéristiques des nouvelles radios au sein d’une pile protocolaire de communication.Durant cette thèse, nous proposons d’étudier de nouveaux protocoles de communication adaptatifs aux conditions du canal et d’interférence visant à la fois l’auto-déploiement de réseaux de capteurs dans des environnements contraignants et l’optimisation de la durée de vie du réseau dans des environnements contraignants.Nous nous concentrerons sur une approche statique dans le cadre de l’automatisation du déploiement de réseaux dans des environnements contraignants. Le protocole détectera, caractérisera et s’adaptera aux conditions du canal (pseudo statique) pour optimiser le bilan de liaison de chaque lien puis diagnostiquera le déploiement.

Today's Wireless Sensors Networks (WSNs) are becoming more mobile and are often deployed in harsh environments. These networks must be autonomous with light maintenance and having an optimized lifetime. Moreover, these networks suffer from interferences between these different technologies (cross) or within the same technology (mutual).The aim of this thesis is to ensure wireless communications the Internet of Things (IoT) with high reliability, energy-efficiency and robustness to interferences by efficiently exploiting the characteristics of last generation transceivers within a communication protocol stack.During this thesis, we propose to study channel and interference aware communication protocols for both self-deployment of WSNs in restrictive and constrained environment and energy efficient optimization.We will focus on a static approach in the context of the network deployment automation in restrictive and constrained environments. The protocol will detect, characterize and adapt to channel conditions to optimize the link budget of each link and then diagnostic the deployment.; Aujourd’hui, les réseaux sans fils sont de plus en plus mobiles et sont déployés dans des environnements souvent très contraignants. Ces réseaux doivent être autonomes avec peu de maintenance et avoir une durée de vie optimisée. De plus, ces réseaux souffrent d’interférence entre les différentes technologies (cross) ou au sein de la même technologie (mutual). L’objectif de cette thèse est de garantir des communications sans fils pour l’internet des Objets (IoT) ultra-fiables, efficaces énergétiquement et robustes aux interférences en exploitant efficacement les caractéristiques des nouvelles radios au sein d’une pile protocolaire de communication.Durant cette thèse, nous proposons d’étudier de nouveaux protocoles de communication adaptatifs aux conditions du canal et d’interférence visant à la fois l’auto-déploiement de réseaux de capteurs dans des environnements contraignants et l’optimisation de la durée de vie du réseau dans des environnements contraignants.Nous nous concentrerons sur une approche statique dans le cadre de l’automatisation du déploiement de réseaux dans des environnements contraignants. Le protocole détectera, caractérisera et s’adaptera aux conditions du canal (pseudo statique) pour optimiser le bilan de liaison de chaque lien puis diagnostiquera le déploiement.

International audience; LoRa is a chirp spread-spectrum modulation that operates in industrial, scientific, and medical (ISM) free bands. The modulation has been developed for low power and long-range wireless Internet of Things (IoT) communications. Operating in unlicensed bands requires connected objects to reduce their energy consumption. Thereby, it is very likely that their access to the radio channel is random, which leads to an increase in the probability of packet collisions. In this paper, we design a new receiver able to decode several IoT LoRa-Like signals simultaneously received on the same channel and with the same spreading factor which leads to destructive collisions. Based on the particular structure of the superposed received signals and the Successive Interference Cancellation (SIC) algorithm, we propose a novel approach to detect, synchronize and decode each of them iteratively.

International audience; Time Difference of Arrival (TDoA) is currently viewed as an important technique for the positioning capabilities in the Internet of Things (IoT). However, in the case of practical measurement, not all the TDoA values between the gateways have the same impact on the localization accuracy. In this paper, a novel TDoA pre-processing methodology for dropping out the outlier TDoA values is presented, after instrumentalizing a paired Cramér-Rao lower bound (CRLB). Thus, the proposed approach is detecting the best TDoA values, which have the lowest paired CRLB values specifically, in the vicinity of the guessed node location, based on a robust thresholding method. A comparison is performed investigating the attainable accuracies for localizing based on this pre-processing algorithm, on a well-defined simulation environment. This simulator is based on a Poisson distribution approach for defining the gateways and node positions, as well as a noise model for emulating the timestamp imperfections. In the given results, the feasibility of the proposed technique is asserted by a drastic improvement over a wide range of the number of gateways as well as measurement noise variances. This manifests the robustness of the contributed method to the outlier TDoA values and its valuable rendering. © 2020 IEEE.

International audience; Low power wide area (LPWA) wireless networks based on the LoRa physical layer have attracted huge attention in recent years, both from industry and from academic researchers. While this rising popularity is due to this technology's demonstrated effectiveness and low cost, unfortunately, due to their complexity, the timing and frequency synchronization algorithms required to detect LoRa-modulated frames, in the context of minimum sampling rate optimum receivers, have received little attention. The aim of this paper is to fill this gap and describe how robust frame detection can be performed while focusing on minimal complexity implementations of the proposed algorithms. The ultimate goal is to propose frame detection techniques applicable to recently proposed ultra-low power software-defined receivers.