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LoRa Communication Technology for IoT Applications—2nd Edition
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LoRa Communication Technology for IoT Applications—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 5354

Special Issue Editor

Dr. Luca Leonardi

E-Mail Website
Guest Editor
Department of Electrical, Electronic and Computer Engineering, University of Catania, 95125 Catania, Italy
Interests: wireless sensor Networks; low power wide area networks; real-time wireless communications; wireless industrial communication; industrial internet of thing; medium access control protocols
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Low-Power Wide-Area Networks (LPWANs) represent a novel communication paradigm that will replace or complement traditional cellular and short-range wireless technologies in several applications. In the Internet of Things (IoT) field, LPWANs are expected to offer energy-efficient connectivity to a high number of low-power devices, distributed over very large geographical areas. In this context, LoRa is a promising LPWAN technology for inter-connecting billions of low-power IoT nodes. We envision that an increasing number of IoT nodes will be deployed and connected to the Internet via LoRa to enable various innovative applications in several domains, including smart cities, smart monitoring, healthcare, and factory automation. We face great practical challenges and research opportunities in the design, implementation, and evaluation of LoRa technology and its applications and system developments.

This Special Issue is focused on LPWAN technologies, and in particular on LoRa, addressing (but not limited to) the following topics:

  • Experimental deployments and solutions for mobile scenarios or situations where devices are deployed on a wide area;
  • Machine learning techniques for the configuration and management of LoRa-based communications;
  • Novel physical layer design and optimization for LoRa;
  • Novel link layer and network layer design and implementation for LoRa;
  • Co-existence and co-operation of LoRa with other wireless technologies in ISM bands;
  • Security aspects of LoRa.

Dr. Luca Leonardi
Guest Editor

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Keywords

  • LoRa
  • LoRaWAN
  • LPWANs
  • IoT and IIoT
  • wide area coverage
  • mobile communications
  • network configuration
  • network management
  • machine learning techniques
  • security

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Related Special Issue

Published Papers (4 papers)

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Research

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22 pages, 1958 KB  
Article
A Novel Multi-Slope Chirp Modulation and Demodulation with Instantaneous Chirp Rate Estimation
by Apiwat Magkeethum, Sukkharak Saechia and Paramote Wardkein
Sensors 2026, 26(9), 2603; https://doi.org/10.3390/s26092603 - 23 Apr 2026
Viewed by 173
Abstract
The growth of Internet of Things (IoT) applications is driving demand for Low-Power Wide-Area Networks (LPWANs) to support higher data rates with the same energy efficiency. While Long Range (LoRa) provides excellent noise immunity and receiver sensitivity, its data rate might be insufficient [...] Read more.
The growth of Internet of Things (IoT) applications is driving demand for Low-Power Wide-Area Networks (LPWANs) to support higher data rates with the same energy efficiency. While Long Range (LoRa) provides excellent noise immunity and receiver sensitivity, its data rate might be insufficient for some applications, including those real-time applications in which LoRa is required to have infrequent transmissions to maintain low power consumption. In this paper, a novel modulation is introduced to address these limitations by utilizing narrowband chirp to represent a data symbol with chirp slopes, called a multi-slope chirp signal. At the receiver, a new blind non-coherent detection technique is also presented to recover the proposed signal. The simulation results confirm that the proposed scheme can successfully transmit information at 2 to 4 bits per symbol, and when compared to LoRa SF 6, it reduces the Time-on-Air (ToA) by half and also achieves an improvement in spectral efficiency in the frequency domain. Full article
(This article belongs to the Special Issue LoRa Communication Technology for IoT Applications—2nd Edition)
55 pages, 3447 KB  
Article
A Microservices-Based Solution with Hybrid Communication for Energy Management in Smart Grid Environments
by Artur F. S. Veloso, José V. Reis, Jr. and Ricardo A. L. Rabelo
Sensors 2026, 26(5), 1714; https://doi.org/10.3390/s26051714 - 9 Mar 2026
Viewed by 622
Abstract
The increasing variability of residential demand, combined with the expansion of distributed generation and electric vehicles, has introduced new challenges to the stability of Smart Grids (SGs). Centralized management models lack the flexibility required to operate under these conditions, reinforcing the need for [...] Read more.
The increasing variability of residential demand, combined with the expansion of distributed generation and electric vehicles, has introduced new challenges to the stability of Smart Grids (SGs). Centralized management models lack the flexibility required to operate under these conditions, reinforcing the need for scalable and data-driven architectures. This study proposes an energy management solution based on microservices, supported by hybrid communication in Low Power Wide Area Networks (LPWAN), integrating Long Range Wide Area Network (LoRaWAN) and LoRaMESH to enhance connectivity, local resilience, and reliability in data acquisition for Internet of Things (IoT) and Demand Response (DR) applications. A prototype composed of a Smart Meter (SM), a Data Aggregation Point (DAP), and a Concentrator (CON) was evaluated in a controlled environment, achieving Packet Delivery Rates above 97%, an average RSSI of −92 dBm, and a Signal-to-Noise Ratio close to 9 dB, validating the robustness of the hybrid communication. At a larger scale, data from 5567 households in the Low Carbon London (LCL) project were used to generate representative Load Profiles (LPs) through seven aggregation and clustering techniques, consistently identifying the 18:00–21:00 interval as the critical peak, with demand reaching up to 42% above the daily average. Fourteen load shifting algorithms were evaluated, and the Hybrid Adaptive Algorithm based on Intention and Resilience (HAAIR), proposed in this work, achieved the best overall performance with a 1.83% peak reduction, US$65.40 in cost savings, a reduction of 60 kg of CO2, a Comfort Loss Index of 0.04, resilience of 9.5, and reliability of 0.98. The results demonstrate that the integration of hybrid LPWAN communication, modular microservice-based architecture, and adaptive DR strategies driven by Artificial Intelligence (AI) represents a promising pathway toward scalable, resilient, and energy-efficient SGs. Full article
(This article belongs to the Special Issue LoRa Communication Technology for IoT Applications—2nd Edition)
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17 pages, 14678 KB  
Article
Preamble Injection-Based Jamming Method for UAV LoRa Communication Links
by Teng Wu, Runze Mao, Yan Du, Quan Zhu, Shengjun Wei and Changzhen Hu
Sensors 2026, 26(2), 614; https://doi.org/10.3390/s26020614 - 16 Jan 2026
Viewed by 596
Abstract
The widespread use of low-cost, highly maneuverable unmanned aerial vehicles (UAVs), such as racing drones, has raised numerous security concerns. These UAVs commonly employ LoRa (Long Range) communication protocols, which feature long-range transmission and strong anti-interference capabilities. However, traditional countermeasure techniques targeting LoRa-based [...] Read more.
The widespread use of low-cost, highly maneuverable unmanned aerial vehicles (UAVs), such as racing drones, has raised numerous security concerns. These UAVs commonly employ LoRa (Long Range) communication protocols, which feature long-range transmission and strong anti-interference capabilities. However, traditional countermeasure techniques targeting LoRa-based links often suffer from delayed response, poor adaptability, and high power consumption. To address these challenges, this study first leverages neural networks to achieve efficient detection and reverse extraction of key parameters from LoRa signals in complex electromagnetic environments. Subsequently, a continuous preamble injection jamming method is designed based on the extracted target signal parameters. By protocol-level injection, this method disrupts the synchronization and demodulation processes of UAV communication links, significantly enhancing jamming efficiency while reducing energy consumption. Experimental results demonstrate that, compared with conventional approaches, the proposed continuous preamble injection jamming method achieves improved signal detection accuracy, jamming energy efficiency, and effective range. To the best of our knowledge, this protocol-aware scheme, which integrates neural network-based signal perception and denoising, offers a promising and cost-effective technical pathway for UAV countermeasures. Full article
(This article belongs to the Special Issue LoRa Communication Technology for IoT Applications—2nd Edition)
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Review

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37 pages, 3630 KB  
Review
Adaptive Antenna for Maritime LoRaWAN: A Systematic Review on Performance, Energy Efficiency, and Environmental Resilience
by Martine Lyimo, Bonny Mgawe, Judith Leo, Mussa Dida and Kisangiri Michael
Sensors 2025, 25(19), 6110; https://doi.org/10.3390/s25196110 - 3 Oct 2025
Cited by 2 | Viewed by 3433
Abstract
Long Range Wide Area Network (LoRaWAN) has become an attractive option for maritime communication because it is low-cost, long-range, and energy-efficient. Yet its performance at sea is often limited by fading, interference, and the strict energy budgets of maritime Internet of Things (IoT) [...] Read more.
Long Range Wide Area Network (LoRaWAN) has become an attractive option for maritime communication because it is low-cost, long-range, and energy-efficient. Yet its performance at sea is often limited by fading, interference, and the strict energy budgets of maritime Internet of Things (IoT) devices. This review, prepared in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, examines 23 peer-reviewed studies published between 2019 and 2025 that explore adaptive antenna solutions for LoRaWAN in marine environments. The work covered four main categories: switched-beam, phased array, reconfigurable, and Artificial Intelligence or Machine Learning (AI/ML)-enabled antennas. Results across studies show that adaptive approaches improve gain, beam agility, and signal reliability even under unstable conditions. Switched-beam antennas dominate the literature (45%), followed by phased arrays (30%), reconfigurable designs (20%), and AI/ML-enabled systems (5%). Unlike previous reviews, this study emphasizes maritime propagation, environmental resilience, and energy use. Despite encouraging results in signal-to-noise ratio (SNR), packet delivery, and coverage range, clear gaps remain in protocol-level integration, lightweight AI for constrained nodes, and large-scale trials at sea. Research on reconfigurable intelligent surfaces (RIS) in maritime environments remains limited. However, these technologies could play an important role in enhancing spectral efficiency, coverage, and the scalability of maritime IoT networks. Full article
(This article belongs to the Special Issue LoRa Communication Technology for IoT Applications—2nd Edition)
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