In this paper, we focus on dynamic random access (DRA) control approaches for machine-type multibeam 5G satellite communications. An important property of a DRA method is to be able to dynamically adapt random access parameters for prevailing backlog load (BLL) conditions. The access points cannot readily know the instantaneous BLL before the RA process is completed and need some simple indirect method to estimate it promptly. To this end we first present an enhancement to indirect BLL estimation that results in a more robust support for the burst traffic changes. Secondly, we evaluate the potential performance gain obtained from the dynamic random access control in a multibeam LEO satellite system that requires beam-level load estimation to work properly in the presence of handovers between moving satellite beams. The results reveal the effectiveness of the proposed DRA approach in multibeam satellite systems in terms of the random access success probability.

Optical Wireless Communication (OWC) and Radio Frequency (RF) heterogeneous networks (HetNets) offer enhanced connectivity by leveraging the complementary advantages of both technologies. Efficient resource allocation in OWC/RF HetNets requires addressing transmission power and coverage disparities, which impact efficiency and service quality, posing challenges to seamless integration. This paper addresses the transmission power allocation problem in OWC/RF HetNets by formulating it as a multi-objective optimization framework. The objectives aim to minimize transmission power for OWC and RF links while maximizing dual-mode data rates. To this end, we propose a novel Q-learning-based framework tailored to multi-objective optimization. Unlike conventional reinforcement learning approaches that aggregate reward functions into a single scalar measure, our method treats reward functions independently by maintaining distinct Q-values for each state-action-reward tuple. Additionally, we introduce an innovative action selection mechanism that simultaneously evaluates multiple Q-values, ensuring balanced decision-making across competing objectives. Extensive simulations validate the proposed framework, demonstrating superior convergence speed, energy efficiency, and adaptability to dynamic network conditions compared to conventional Q-learning methods.

Satellite communications have emerged as one of the most feasible solutions to provide global wireless coverage and connect the unconnected. Starlink dominates the market with over$\mathbf{7,000}$operational satellites in low Earth orbit (LEO) and offers global high-speed and low-latency Internet service for stationary and mobile use cases, including in-motion connectivity for vehicles, vessels, and aircraft. Starlink terminals are designed to handle extreme weather conditions. Starlink recommends a flat high performance (FHP) terminal for users living in areas with extreme weather conditions. The earlier studies evaluated Starlink's FHP throughput for stationary and in-motion users without providing a detailed analysis of how weather affects its performance. There remains a need to investigate the impact of weather on FHP's throughput. In this paper, we address this shortcoming by analyzing the impact of weather on Starlink's performance in Oulu, Finland, a city located in Northern Europe near the Arctic Circle. Our measurements reveal that rain degrades median uplink and downlink throughput by 52.27% and$\mathbf{37.84 \%}$, respectively. On the contrary, there was no noticeable impact on the round-trip time. Additionally, we also examine the impact of cloud cover on the Starlink throughput. The linear regression analysis reveals the negative relationship between throughput and cloud cover. The cloud cover of up to 12.5% has around 20% greater throughput than the cloud cover of 87.5%.

This paper presents a novel multi-attribute decision-making approach for managing handovers in Optical Wireless Communication/Radio Frequency Heterogeneous Networks (OWC/RF HetNets). The proposed method systematically evaluates potential Access Points (APs) using multiple criteria, including fixed and variable handover costs, the ratio of the node's data rate demand to the achievable rate from APs, and the ratio of the utilized capacity of APs. Using local parameters, nodes assess these attributes over a finite future horizon and construct a decision matrix. The VIKOR method is then applied to decide whether to initiate a handover to a new AP or remain connected to the current one. Simulation results show that the proposed decentralized scheme effectively manages handovers, leading to improved load balancing and reduced handover latency in OWC/RF HetNets.

Cooperative Awareness (CA) is an integral part of Intelligent Transport Systems (ITSs) standardized by the European Telecommunications Standards Institute (ETSI) and targeted to ensure safe and efficient transportation in the future. Miniature Unmanned Aerial Vehicles (UAVs) have been widely utilized in various applications due to their ever-increasing functionalities. Thus, it is a matter of time until the need to integrate them into ITS and human-centric communication ecosystems arises. To enable the benefits of ITS to miniature UAVs, in this paper, a low-cost, low-power, novel UAV-CA Message (CAM) scheme for indoor and outdoor based on Bluetooth Low Energy (BLE) radio access technology is introduced. Furthermore, a proof-of-concept implementation is developed for this BLE-based UAV-CAM, and its performance is investigated using analytical, experimental, and simulation methods. Notably, both the performance for CA over BLE4 legacy advertising and the extended advertising introduced in BLE5 are reported. Our results demonstrate that BLE is able to produce a power-efficient, scalable solution with sufficient range capabilities while keeping up with the traffic requirements of CAM.

This paper introduces an enhancement to the Long-Range Frequency-Hopping Spread Spectrum (LR-FHSS), a modulation within the LoRaWAN specification, particularly useful in dense networks supported by satellite gateways. LR-FHSS replicates headers and payload fragments across different physical channels, but the distinct transmission strategies for headers and payloads can lead to uneven success rates and degrading performance. To address this, we propose a scheme that allocates orthogonal physical channels for headers and payloads. Through analytical and simulation results, considering factors such as payload size and the number of users, we identify the optimal distribution of channels between headers and payloads to maximize success probability. The proposed scheme significantly improves performance, supporting up to 50% more users at the same reliability level as the standard LR-FHSS.

During the past years, the LoRaWAN technology took a prominent position among the wireless connectivity solutions for the Internet of Things (IoT) and has attracted substantial attention. The LoRaWAN technology has become popular for collecting the data from the sensors, which traditionally have periodic communication patterns. Meanwhile, recent studies have shown that the LoRaWAN procedures, such as the over-the-air activation, may also compromise the uniformity of data traffic distribution. Therefore, in this study, we investigate how the communication pattern of LoRaWAN devices during activation and data communication affects the overall network performance with respect to speed of activation and overall packet delivery probability. We show that the periodic communication patterns, widely employed by commercial LoRaWAN devices today, are less efficient than the patterns featuring random delays between the packets. Also, we find that introduction of a random delay between uplink data packets helps randomizing the channel access and enables network performance boost both for the application data transfer and during the activation. Finally, we show that implementation of the suggested communication patterns modification is feasible for the state-of-the-art LoRaWAN transceivers with no hardware modifications.

Low-power wide-area networks (LPWANs) have become an important enabler for the Internet of Things (IoT) connectivity. Application domains, such as smart cities, smart agriculture, intelligent logistics, and transportation, require communication technologies that combine long transmission ranges and energy efficiency. Recent and future trends make the long-range wide-area network (LoRaWAN) and narrowband-IoT (NB-IoT) the most prospective drivers of the IoT business. In this article, after discussing the main features of the two technologies, we carry out a fair quantitative comparison between the two, investigating different performance indicators, in order to guide designers in the selection of the most appropriate technology, depending on the application requirements.

An assessment of radio network coverage, usually in the form of a measurement campaign, is essential for multibase-station (multi-BS) network deployment and maintenance. It can be conducted by a network operator or its served consumers. However, the number of measurement points and their locations may not be known in advance for an efficient and accurate evaluation. The main goal of this study is to propose a new methodology for understanding the selection of measurement points during coverage and signal quality assessment. It is particularly tailored to multi-BS low-power wide-area network (LPWAN) deployments without explicit knowledge of BS locations. To this aim, we first conduct a large-scale measurement campaign for three popular LPWAN technologies, namely, narrowband IoT (NB-IoT), Sigfox, and LoRaWAN. Utilizing this baseline data, we develop a procedure for identifying the minimum set of measurement points for the coverage assessment with a given accuracy as well as study which interpolation algorithms produce the lowest approximation error. Our results demonstrate that a random choice of measurement points is on par with their deterministic selection. Out of the candidate interpolation algorithms, the Kriging method offers attractive performance in terms of the absolute error for NB-IoT deployments. In contrast, for Sigfox and LoRaWAN infrastructures, less complex techniques, such as the natural neighbor, linear interpolation, or inverse-distance weighting, can achieve comparable (and occasionally even better) accuracy levels.

The offshore wind farms are gaining momentum due to their promise to offer sustainable energy with low pollution and greenhouse gas emission. However, despite all the immense technological progress of recent years, the operation in a harsh and hard-to-reach environment remains challenging. According to the reports, each offshore wind turbine requires five maintenance visits a year on average, and the cumulative repair costs constitute around 30% of the turbine’s life-cycle expenditure. Motivated by the advancement of massive machine-type connectivity (mMTC) and satellite technologies, in this study, we investigate the potential of these to enable remote monitoring of the offshore wind farms. Specifically, the two alternative architectures are considered. The indirect architecture relies on using a local mMTC gateway (GW) with a backbone over a reliable communication channel (e.g., satellite or wire-based). The direct approach implies the transmission of the data by sensors on the wind turbines directly to the mMTC GW on the low-Earth-orbit satellite. The details of the system design, the alternative implementation strategies, and relevant pros, cons, and tradeoffs are pin-pointed. Finally, we employ simulations using realistic deployment and traffic and advanced propagation and collision models to characterize these two approaches’ feasibility and packet delivery probability numerically when implemented over LoRaWAN mMTC technology.

In this paper, we conceptualise and propose integrating UAVs with Intelligent Transportation Systems (ITS) based on using the Cooperative-ITS (C-ITS) framework. We start by discussing the state of the art and pinpointing some of the reasons for integration and the applications that the envisaged integration would enable. Next, we recall the critical aspects of the state of the art C-ITS connectivity and discuss how seamless integration of UAVs into C-ITS can be achieved. Notably, we show that encapsulation of UAVs in C-ITS does not imply significant changes for the currently existing mechanisms and data formats. Finally, we discuss some of the open research challenges related to the integration and operation of the integrated systems and pinpoint some mechanisms which can help to address these.

In this paper, we study real-world performance of Sigfox, which is one of the most mature Low-Power Wide-Area Network (LPWAN) technologies that operate in unlicensed frequency bands. During an extensive measurement campaign conducted over three months in the city of Brno, Czech Republic, we assessed the communication performance and the radio channel properties in 311 different test locations. We observed that despite the challenging natural landscape and urban environment of the test area, more than 94% of the packets sent were received successfully, with at least one packet delivered from 297 out of 311 tested locations. Our results also reported experiment-based radio channel and signal-to-noise characterization as well as provided insights into the efficiency of two crucial mechanisms used by Sigfox to improve the packet delivery - packet repetition and multi-gateway reception. Finally, we employed our experimental data to understand the efficiency of two non-fingerprint localization methods based on received signal strength indicator in a practical Sigfox network.

In this paper, we consider a NarrowBand-Internet of Things (NB-IoT) network where an Unmanned Aerial Vehicle (UAV) is employed to gather data from IoT devices deployed in a given area. It is well known that UAVs may fly over the terrestrial plane, where and when needed, acting as Unmanned Aerial Base Stations (UABs). In order to serve as many ground IoT devices as possible, a proper trajectory design is fundamental. As we show in the paper, the optimization of the UAV speed and the radio parameters are also essential. Specifically, this paper studies a cluster-based scenario, where IoT devices are deployed according to a Thomas process, and applies a Traveling Salesman Problem approach to design the UAB trajectory. Notably, our model considers the protocol constraints on the number of resource units available on the UAB's NPUSCH, and the data rate that it can provide to IoT devices. Our results reveal the impact of different design parameters, such as UAB speed and NPRACH periodicity on the network throughput and the number of requests served.

A remarkable progress in the Low Power Wide Area Network (LPWAN) technologies over the recent years opens new opportunities for developing versatile massive Internet of Things (IoT) applications. In this paper, we focus on one of the most popular LPWAN technologies operating in the license-exempt frequency bands, named LoRaWAN. The key contribution of this study is our unique set of results obtained during an extensive measurement campaign conducted in the city of Brno, Czech Republic. During a three-months-period, the connectivity of a public Long Range Wide Area Network (LoRaWAN) with more than 20 gateways (GWs) was assessed at 231 test locations. This paper presents an analysis of the obtained results, aimed at capturing the effects related to the spatial diversity of the GW locations and the real-life multi-GW network operation with all its practical features. One of our findings is the fact that only for 47% tested locations the GW featuring the minimum geographical distance demonstrated the highest received signal strength and signal-to-noise ratio (SNR). Also, our results captured and characterized the variations in the received signal strength indicator (RSSI) and SNR as a function of the communication distance in an urban environment, and illustrated the distribution of the spreading factors (SFs) as a result of the adaptive data rate (ADR) algorithm operation in a real-life multi-GW deployment.

In recent years, many new radio-based connectivity solutions for the Internet of Things (IoT) have been proposed. At the same time, development towards the 6G has brought on the stage the new business concepts. One of them is the concept of a micro-operator and implies the local entities to act as the telecom infrastructure owner and provider in their premises. In the current paper, we discuss the deployment and report the practical performance of a single-cell NB-IoT deployed as a part of the 5G Test Network (5GTN) and controlled by a smart-campus micro-operator. The practical measurements reported in the paper have been carried in the University of Oulu within a huge interconnected indoor environment with the total floor area of 188 600 m2. Our results demonstrate that the NB-IoT technology is a viable connectivity solution for various non-critical machine-based applications deployed indoors, highlight the practical performance of this technology, and reveal some practical specifics and challenges of acting as an IoT micro-operator.

Myriads of new devices take their places around us every single day, making a decisive step towards bringing the concept of the Internet of Things (IoT) in reality. The Low Power Wide Area Networks (LPWANs) are today considered to be one of the most perspective connectivity enablers for the resource and traffic limited IoT. In this paper, we focus on one of the most widely used LPWAN technologies, named LoRaWAN. Departing from the traditional data-focused security attacks, in this study we investigate the robustness of LoRaWAN against energy (depletion) attacks. For many IoT devices, the energy is a limited and very valuable resource, and thus in the near future the device's energy may become the target of an intentional attack. Therefore, in the paper, we first define and discuss the possible energy attack vectors, and then experimentally validate the feasibility of an energy attack over one of these vectors. Our results decisively show that energy attacks in LoRaWAN are possible and may cause the affected device to lose a substantial amount of energy. Specifically, depending on the device's SF (Spreading Factor), the demonstrated attack increased the total energy consumption during a single communication event 36% to 576%. Importantly, the shown attack does not require the attacker to have any keys or other confidential data and can be carried against any LoRaWAN device. The presented results emphasize the importance of energy security for LPWANs in particular, and IoT in general.

The paper introduces a LoRaWAN simulation model implemented for the Riverbed Modeler (former OPNET modeler suite). First, the key components of the developed simulator solution are detailed. Then, the results of the simulator's validation for several test scenarios are presented. The developed simulator is used to investigate the effect of collision models on the results of LoRaWAN performance simulation. Specifically, the three models are studied: a baseline - implying loss off all colliding packets, an intra spreading factor (SF) with capture effect, and intra/inter SF with capture effect. The simulations verify that the results of the baseline model are in line with that for pure Aloha, while the two other demonstrate up to two-three fold higher delivery ratio. The obtained results illustrate the substantial impact of the collision model on the accuracy of simulations and motivate the need for further practical studies for the collision and interference mechanisms within a LoRaWAN network. Based on the results obtained through simulations, several drawbacks related to the use of strictly periodic traffic in LoRaWAN networks are noted.

The last years brought many novel challenges for the Internet of Things (IoT). Low capital and operational expenditures, massive deployments of devices, reliability and security are among the most crucial ones. The recently introduced Low-power wide area (LPWA) technologies provide one possible way of addressing these challenges. In the current paper, we focus on one of the most mature LPWA technology, namely Sigfox. We provide a brief security assessment of this technology and highlight the main security imperfections. Notably, we also consider the recent changes introduced in the last revision of the Sigfox specification released in the fourth quarter of 2017. Importantly, this paper discusses the highlighted issues and compares three selected cryptographic encryption solutions (AES, ChaCha and OTP) in respect to the main IoT triad of performance, security and cost. We investigate the encryption solutions and characterize their energy consumption in a real-life implementation. The results herein presented are useful for understanding the cost of enabling security aspects and enable selecting the most efficient encryption protocol.

The landscape of the contemporary IoT radio access technologies (RATs) is excessively diverse, especially when it comes to such a complex environment as Smart City. On the one hand, this diversity offers operators sufficient flexibility to select the most appropriate RAT for their target application. On the other hand, it becomes a severe limiting factor leading to high level of uncertainty for the IoT device vendors, who need to decide, which technology to support in their hardware. In this paper, we consider the provisioning of the low-power wide area network (LPWAN) devices supporting multiple RATs. First, we briefly discuss the parameters of several potential radio technologies as well as analyze the pros and cons of combining them in a single device. Next, we prototype a real-life device capable of communicating via two perspective LPWAN technologies, namely, LoRaWAN and NB-IoT, and report on the initial results of its performance evaluation. These confirm the feasibility of instrumenting dual-mode devices as well as reveal several important aspects related to the development of multi-radio IoT equipment and its performance. In our view, due to their higher flexibility, reliability, and dependability, the devices such as the one developed can be beneficial for various Smart City applications, with smart energy grids and road traffic control being only two of many examples.

It is expected that the number of the Internet of Things (IoT) devices will grow significantly in the coming years. Batteries, which are today the most common source of energy supply for these devices, have many limitations. The limited capacity and the negative environmental effect of their production and recycling are among the most crucial ones. Energy harvesting has been proposed to overcome this problem. Over the past decade, the academia has produced thousands of papers on this topic, but it is still difficult to find a commercial sensor node operating solely with energy harvesting. One of the major reasons for this is the highly opportunistic and unreliable nature of the energy income from most of the available ambient energy sources. In this paper, we address this problem by proposing a control loop enabling an energy harvesting sensor to request a recharge whenever needed. Energy-wise, the proposed method effectively transforms the operation mode of a passive wireless device from opportunistic to proactive, thus enabling an application to operate in a more predictable manner. The feasibility and efficiency of the proposed approach is demonstrated by implementing a real-life prototype Bluetooth Low Energy capable sensor node equipped with photovoltaic energy harvester, which can communicate and request a recharge from a commercial indoor smart lighting system.

Today the LoRaWAN is among the most widely adopted Low Power Wide Area Network (LPWAN) technologies. In contrast to the other alternatives, LoRaWAN enables deploying both continent-wide public networks, and private networks composing one or several gateways. In this paper, we empirically investigate how does the presence of the downlink traffic affects the performance of uplink for LoRaWAN operating in 868 MHz EU bands. Our results show that in real-life the downlink transmissions can compromise performance of uplink and must be accounted for when planning a network. Also we demonstrate the effects that the selection of secondary frequency channels and data rates have on the performance of a LoRaWAN network. The reported results reveal new dependences and provide the ground truth reference for the future analytical works. For these reasons, the paper can be of interest to both practitioners, planning and deploying LoRaWAN networks, and the researchers performing analytical work on LoRaWAN.

Internet of Things (ioT) drives today's world towards digitalization allowing diverse and innovative use cases. These use cases are changing in a fundamental way how people are conducting their business in various verticals. In this paper we focus on the real estate use case. We deploy a monitoring system in a large open space at University of Oulu. The deployed system visualizes real estate conditions of this environment and gives insight to understanding a LoRaWAN IoT-enabled building. The number of the sensor nodes composing the deployed system reaches 331, with each node comprising five sensors providing information about temperature, humidity, CO2, amount of light, and motion. In the paper we report the results and the lessons learned during the deployment of such an extensive LoRaWAN sensor network. Aside of the practicalities related to the deployment of the network, we characterize and report the performance of the deployed network. The conducted deployment can become a valuable reference for engineers and practitioners, deploying a real estate monitoring system with LoRaWAN.

Bluetooth Low Energy (BLE) devices are becoming common in hospital scenarios. This technology is widely employed to collect patients' vital signs, to provide wireless connectivity to medical equipment, and to enable communications between devices carried by hospital personnel, patients and visitors. This paper presents a mathematical model to evaluate the impact of the interferences, from different wireless technologies, on the performance of a BLE-based body area networks operating over the 1 Mbit/s physical layer (PHY). The interfering technologies addressed are ZigBee (802.15.4), Wi-Fi (802.11), and the newly introduced BLE version 5.0 (coded PHY). The results for the latter are supported by real-life measurements, which are reported in this paper, thus giving some insight into the practical performance of this new technology. The presented numerical results provide guidance on how to manage these various technologies to minimize the packet error rate (PER) of the communications emanating from the on-body BLE enabled devices.

The major focus of the low power wide area networks (LPWAN) is to provide energy efficiency and large coverage to Internet of Things (IoT) applications that do not require a large bandwidth. There are several LPWAN technologies that can enable these functionalities such as SigFox, LoRa Wide Area Network (LoRaWAN), Narrowband-IoT (NB-IoT), and Weightless. The estimates of the number of wireless IoT devices in the near future are between 20 Billion to even 75 Billion. At the very same time the development and deployment of the 5th generation of mobile networks (5G) is rolling out. Among others, the new technology will deliver huge capacity which can be employed for enabling the backbone connectivity for LPWAN. Therefore, there is a need to have possibility to seamlessly integrate LPWANs with the upcoming 5G. In this work, we investigate how one can integrate the LoRaWAN with the 5G Test Network (5GTN) running in the University of Oulu, Finland. Furthermore, one of the options discussed is implemented in practice and its operation is verified. At the moment the implementation is used for wide range of other research activities beside this work, enabling a third party to bring their LoRaWAN compliant devices for testing and application development.

Efficiency and flexibility are among the key requirements for Wireless Sensor and Actuator Networks (WSAN) of Internet of Things (IoT) era. In this work we present and demonstrate a novel WSAN and IoT platform. The new nodes are constructed by stacking together the different hardware modules encapsulating power sources, processing units, wired and wireless transceivers, sensors and actuators, or sets of those. Once a node is built, its processing unit can automatically identify all the connected hardware modules, obtain required software modules and tune node's operation accounting for its structure, available resources and active applications.

In the paper we present and demonstrate the modular prototyping platform designed for trialing the Internet of Things (IoT) applications. The new devices are constructed by stacking together the various hardware modules encapsulating power sources, processing units, wired and wireless transceivers, sensors and actuators, or sets of those. The main processing unit automatically identifies all the attached modules and adjusts own operation accordingly. The demo will showcase how the platform can be used for building up multi-radio technology enabled wireless devices which will automatically form a heterogeneous wireless sensor and actuator network (WSAN). The possible use case scenarios and the ongoing research activities around the platform will be highlighted as well.

Bluetooth Low Energy (BLE) is a recently developed energy-efficient short-range radio communication technology, which is currently vastly gaining popularity and which might become an enabler for implementing in practice the Internet of Things (IoT) concept. However, the complexity of the protocol and the lack of the simulation tools impedes the studies of BLE network performance. For this reason, in the paper we introduce the novel simulation tool, which is capable of simulating the communication in the networks of BLE devices. In the paper we discuss the capabilities and limitations of the suggested tool and compare the results of the simulations with the ones obtained with the real-life hardware BLE transceivers. Also, the paper highlights some of the results obtained with the developed tool, which disclose the effect of the communication parameters on the performance of the BLE protocol in the multi-node scenarios and point out few weak points of the BLE technology.

In the paper we focus on the problem of improving the efficiency of the peer-to-peer connection establishment for the recently suggested Bluetooth Low Energy (BLE) protocol. We suggest a novel Accelerated Connection Establishment (ACE) mechanism which enables to significantly reduce the time and energy consumption for establishing the connection between BLE devices in the multi-node scenarios. We discuss in details the background of the problem, introduce the suggested solution, and present the results of BLE network simulations, which confirm the efficiency of the suggested mechanism.

The technology advances over the recent years brought on market many portable consumer and telecommunication electronic devices, most of which utilize low-power embedded systems. Significant part of these devices is nowadays supplied from the primary batteries, among which the alkaline ones are the most widespread. The paper presents the real-life discharge curves and measurement results of available energy for various commercially available off-the-shelf alkaline batteries under continues and intermittent discharge. The specifics of the paper is that it focuses the battery discharge profiles, which are typical for the portable devices based on low-power micro controllers in general and Wireless Sensor Network (WSN) nodes in particular. Therefore, provided in the paper data is valuable both for engineers for estimating their devices' lifetimes and for researchers for evaluating battery models or estimating performance for energy efficiency improvement mechanisms. Besides, the presented results reveal importance of battery characteristics consideration for lifetime improvement and demonstrate need for energy-source aware optimization algorithms for battery supplied systems in general and for WSN especially.