New verticals within the Internet of Things (IoT) paradigm such as smart cities, smart farming, or goods monitoring, among many others, are demanding strong requirements to the Radio Access Network (RAN) in terms of coverage, end-node’s power consumption, and scalability. The technologies employed so far to provide IoT scenarios with connectivity, e.g., wireless sensor network and cellular technologies, are not able to simultaneously cope with these three requirements. Thus, a novel solution known as Low Power - Wide Area Network (LP-WAN) has emerged as a promising alternative to provide with low-cost and low-power-consumption connectivity to end-nodes spread in a wide area. Concretely, the Long-Range Wide Area Network (LoRaWAN) technology is one of the LP-WAN platforms that is receiving greater attention from both the industry and the academia. For that reason, in this work, a comprehensive performance evaluation of LoRaWAN under different environmental conditions is presented. The results are obtained from three real scenarios, namely, urban, suburban, and rural, considering both dynamic and static conditions, hence a discussion about the most proper LoRaWAN physical-layer configuration for each scenario is provided. Besides, a theoretical coverage study is also conducted by the use of a radio planning tool considering topographic maps and a precise propagation model. From the attained results, it can be concluded that it is necessary to evaluate the propagation conditions of the deployment scenario prior to the system implantation in order to reach a compromise between the robustness of the network and the transmission data-rate.

The emergence of low-cost connected devices is enabling a new wave of sensorization services. These services can be highly leveraged in industrial applications. However, the technologies employed so far for managing this kind of system do not fully cover the strict requirements of industrial networks, especially those regarding energy efficiency. In this article a novel paradigm, called Low-Power Wide Area Networking (LP-WAN), is explored. By means of a cellular-type architecture, LP-WAN–based solutions aim at fulfilling the reliability and efficiency challenges posed by long-term industrial networks. Thus, the most prominent LP-WAN solutions are reviewed, identifying and discussing the pros and cons of each of them. The focus is also on examining the current deployment state of these platforms in Spain. Although LP-WAN systems are at early stages of development, they represent a promising alternative for boosting future industrial IIoT (Industrial Internet of Things) networks and services.

In recent years, the growing development of Connected Autonomous Vehicles (CAV), Intelligent Transport Systems (ITS), and 5G has led to the emergence of Autonomous Intersection Management (AIM) systems. AIM presents a new paradigm for CAV control at future intersections, allowing safe and efficient traffic flows, eliminating traffic signals, and focusing on the complex dynamics of real-life situations. So far, the development of AIM algorithms has been based on basic control algorithms, without the ability to adapt or keep learning new situations. This makes the proposed AIM incapable of dealing with complex tasks. In this paper, we present a new advanced approach to AIM based on end-to-end Multi-Agent Deep Reinforcement Learning (MADRL) and trained via Curriculum through Self-Play, called advanced Reinforced AIM (adv.RAIM). adv.RAIM can autonomously learn the complex dynamics of real-life traffic and provides a new path for building smarter AIM capable of proactively controlling CAV speed at intersections. The results show impressive improvements when compared to traffic light control techniques, as well as outperforming other recently proposed AIMs, highlighting the advantages of using MADRL.

The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links.

As quantum computing advances, current cryptographic protocols are increasingly vulnerable to quantum attacks, particularly those based on Public Key Infrastructure (PKI) like RSA or Elliptic Curve Cryptography (ECC). This paper presents a comprehensive review of Post-Quantum Cryptography (PQC) as a solution to protect digital systems in the quantum era. We provide an in-depth analysis of various quantum-resistant cryptographic algorithms, including lattice-based, code-based, hash-based, isogeny-based, and multivariate approaches. The review highlights the National Institute of Standards and Technology (NIST) PQC standardization process, highlighting key algorithms, such as CRYSTALS–Kyber, CRYSTALS–Dilithium, Falcon, and SPHINCS+, and discusses the strengths, vulnerabilities, and implementation challenges of the leading algorithms. In addition, we explore transition strategies for organizations, emphasizing hybrid cryptography to ensure backward compatibility during migration. This study offers key insights into the future of cryptographic standards and the critical steps necessary to prepare for the transition from classical to quantum-resistant systems.

The huge growth in the number of connected wireless devices leads to an increasing demand for network connectivity. In this context, aerial networks may play an important role by widening the concept of access networks. This paper describes and analyzes one of the most promising applications of Unmanned Aerial Vehicles, commonly known as drones, in the field of communications: Extending the capacity or coverage of wireless systems through the deployment of aerial communication networks. We present a comprehensive characterization study of an experimental system to deploy an aerial WiFi network. To do so, an Intel Galileo development board is appropriately configured and equipped as a WiFi node playing either the role of an access point in the infrastructure mode or of an intermediate hop in the ad-hoc operational mode. This device is then integrated onboard a drone. We compare both WiFi modes in terms of coverage area, throughput, and energy efficiency. Preliminary results reveal that there is a trade-off between coverage and data rates, for which the infrastructure mode performs better, and energy efficiency, where the ad-hoc mode is more responsive.