Добірка наукової літератури з теми "LR-FHSS"

Long-range frequency hopping spread spectrum (LR-FHSS) is a pivotal advancement in the LoRaWAN protocol that is designed to enhance the network’s capacity and robustness, particularly in densely populated environments. Although energy consumption is paramount in LoRaWAN-based end devices, this is the first study in the literature, to our knowledge, that models the impact of this novel mechanism on energy consumption. In this article, we provide a comprehensive energy consumption analytical model of LR-FHSS, focusing on three critical metrics: average current consumption, battery lifetime, and energy efficiency of data transmission. The model is based on measurements performed on real hardware in a fully operational LR-FHSS network. While in our evaluation, LR-FHSS can show worse consumption figures than LoRa, we find that with optimal configuration, the battery lifetime of LR-FHSS end devices can reach 2.5 years for a 50 min notification period. For the most energy-efficient payload size, this lifespan can be extended to a theoretical maximum of up to 16 years with a one-day notification interval using a cell-coin battery.

The term "Industry 4.0," or the "fourth industrial revolution," is used to describe a period of significant technological advancement within the manufacturing sector. This revolution is characterized by the integration of advanced technologies, including artificial intelligence, robotics, augmented reality, additive manufacturing, the Internet of Things (IoT), big data, and cybersecurity, into the manufacturing processes. In this context, the IoT plays a pivotal role in the collection and transmission of data in real-time, thereby facilitating informed decision-making and process optimization. Nevertheless, the implementation of this technology is confronted with considerable challenges pertaining to connectivity, particularly in remote locations. Low Earth Orbit (LEO) satellites have been identified as an effective solution, providing global connectivity and support for IoT applications in inaccessible regions. The present study conducts a systematic review of research on the use of LEO satellite constellations, addressing issues of coverage, latency, protocols, and data transmission efficiency for the IoT. A search of databases such as Scopus and Google Scholar, conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) methodology, yielded forty relevant articles for analysis. The results underscore the significance of Low Power Wide Area Networks (LPWAN), protocols such as Long Range (LoRa) and Long-Range Frequency Hopping Spead Spectrum (LR-FHSS) in IoT satellite communication, while also highlighting the challenges and advances in integrating space and terrestrial networks. Consequently, this review serves as a valuable foundation for future research and practical applications in Industry 4.0.

Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) is a new physical layer option that has been recently added to the LoRa family with the promise of achieving much higher network capacity than the previous versions of LoRa. In this paper, we present our evaluation of LR-FHSS based on real-world packet traces collected with an LR-FHSS device and a receiver we designed and implemented in software. We overcame challenges due to the lack of documentations of LR-FHSS and our study is the first of its kind that processes signals transmitted by an actual LR-FHSS device with practical issues such as frequency error. Our results show that LR-FHSS meets its expectations in communication range and network capacity. We also propose customized methods for LR-FHSS that improve its performance significantly, allowing our receiver to achieve higher network capacity than those reported earlier.

Cette recherche se concentre sur l'amélioration des communications des réseaux à large bande basse consommation (LP-WAN) en utilisant des technologies de radio cognitive. Plus précisément, elle aborde le défi de la localisation du réseau en utilisant l'indicateur de force du signal reçu (RSSI) des réseaux LoRa, ainsi que l'algorithme ML-MTL proposé, pour améliorer la précision de l'estimation de la position des dispositifs finaux. De plus, cette étude explore l'estimation et l'extension de la couverture LoRaWAN. En ce qui concerne l'estimation de la couverture, elle démontre que la collecte de plusieurs points de données autour de chaque passerelle permet de créer des cartes thermiques de couverture précises grâce à un algorithme d'estimation de la couverture LoRaWAN proposé. Cette approche permet de localiser efficacement les zones où des passerelles supplémentaires sont nécessaires pour améliorer la fiabilité du réseau. Pour l'extension de la couverture, l'étude se concentre sur l'optimisation de la couverture terrestre des LP-WAN par le biais de stratégies basées sur des relais. En intégrant des techniques de radio cognitive, la recherche vise à étendre la zone de couverture des réseaux LoRa, améliorant à la fois la portée et la fiabilité des services de communication. En termes de communication par satellite, le projet utilise Omnet++ pour simuler la performance et la latence des réseaux LoRa dans un environnement satellite. La simulation évalue la faisabilité de l'utilisation des réseaux LoRa dans les communications par satellite, mettant en évidence son potentiel pour étendre les capacités des LP-WAN aux régions éloignées ou difficiles d'accès par le biais de liaisons satellites. En abordant à la fois les domaines terrestre et satellite, cette recherche adopte une approche globale pour faire progresser les communications LP-WAN. L'intégration des techniques de radio cognitive contribue au développement de systèmes de communication intelligents et adaptatifs qui améliorent l'efficacité, la fiabilité et la couverture dans les environnements LP-WAN terrestres et par satellite
This research focuses on improving Low-Power Wide-Area Network (LP-WAN) communications using cognitive radio technologies. Specifically, it addresses the challenge of network localization by utilizing the Received Signal Strength Indicator (RSSI) from LoRa networks, along with the proposed ML-MTL algorithm, to improve the accuracy of end device position estimation. Additionally, this study explores LoRaWAN coverage estimation and extension. In coverage estimation, it demonstrates that gathering multiple data points around each gateway enables the creation of accurate coverage heat maps using a proposed LoRaWAN coverage estimation algorithm. This approach effectively pinpoints areas where additional gateways are needed to improve network reliability. For coverage extension, the study focuses on optimizing terrestrial LP-WAN coverage through relay-based strategies. By incorporating cognitive radio techniques, the research aims to expand the coverage area of LoRa networks, enhancing both the reach and reliability of communication services. In terms of satellite communication, the project employs Omnet++ to simulate the performance and latency of LoRa networks in a satellite environment. The simulation assesses the feasibility of using LoRa networks in satellite communications, highlighting its potential for extending LP-WAN capabilities to remote or hard-to-reach regions through satellite links. By addressing both terrestrial and satellite domains, this research adopts a comprehensive approach to advancing LP-WAN communications. The integration of cognitive radio techniques contributes to the development of intelligent, adaptive communication systems that enhance efficiency, reliability, and coverage across terrestrial and satellite LP-WAN environments