Search Results (220)

The increasing demand for sustainable and renewable energy solutions has made radio frequency energy harvesting (RFEH) a promising technique for powering low-power electronic devices. RFEH captures ambient RF signals from wireless communication systems, such as mobile networks, Wi-Fi, and broadcasting stations, and converts them into usable electrical energy. This approach offers a viable alternative for battery-dependent and hard-to-recharge applications, including streetlights, outdoor night/security lighting, wireless sensor networks, and biomedical body sensor networks. This article provides a comprehensive review of the RFEH techniques, including state-of-the-art rectenna designs, energy conversion efficiency improvements, and multi-band harvesting systems. We present a detailed analysis of recent advancements in RFEH circuits, impedance matching techniques, and integration with emerging technologies such as the Internet of Things (IoT), 5G, and wireless power transfer (WPT). Additionally, this review identifies existing challenges, including low conversion efficiency, unpredictable energy availability, and design limitations for small-scale and embedded systems. A critical assessment of current research gaps is provided, highlighting areas where further development is required to enhance performance and scalability. Finally, constructive recommendations for future opportunities in RFEH are discussed, focusing on advanced materials, AI-driven adaptive harvesting systems, hybrid energy-harvesting techniques, and novel antenna–rectifier architectures. The insights from this study will serve as a valuable resource for researchers and engineers working towards the realization of self-sustaining, battery-free electronic systems. Full article

5G private mobile networks are becoming a platform for ‘wire-free’ networking for professional applications in smart industry sectors, such as automated warehousing, logistics, autonomous vehicle deployments in campus environments, mining, material processing, and more. It is expected that most of these Machine-to-Machine (M2M) and Industrial Internet of Things (IIoT) communication paths will be realized wirelessly, as the advantages of providing flexibility are obvious compared to hard-wired network installations. Unfortunately, the deployment of private 5G networks in smart industries has faced delays due to a combination of high costs, technical challenges, and uncertain returns on investment, which is reflected in troublesome access to fully operational private networks. To obtain insight into occupational exposure to radiofrequency electromagnetic fields (RF EMF) emitted by 5G private mobile networks, an analysis of RF EMF due to different types of 5G equipment was carried out on a real case scenario in the production and logistic (warehouse) industrial sector. A private standalone (SA) 5G network operating at 3.7 GHz in a real industrial environment was numerically modeled and compared with in situ RF EMF measurements. The results show that RF EMF exposure of the workers was far below the existing exposure limits due to the relatively low power (1 W) of indoor 5G base stations in private networks, and thus similar exposure scenarios could also be expected in other deployed 5G networks. In the analyzed RF EMF exposure scenarios, the radio transmitter—so-called ‘radio head’—installation heights were relatively low, and thus the obtained results represent the worst-case scenarios of the workers’ exposure that are to be expected due to private 5G networks in smart industries. Full article

The performance of multiple-input single-output (MISO) transmission is highly dependent on the accuracy of the channel state information (CSI) at the base station (BS), which necessitates precise CSI estimation and reliable feedback from the user equipment. However, the overhead of the CSI feedback occupies substantial uplink bandwidth resources. To alleviate the overhead, this paper proposes a novel task-based quantizer for uplink MISO visible light communication (VLC) systems. In particular, a hybrid radio frequency (RF)/VLC system is considered, where VLC links are mainly used for large-volume downlink transmissions and RF links are used for uplink CSI feedback. Since the RF bandwidth resources are limited, the CSI is quantified to reduce the uplink resource requirements, which, however, inevitably causes CSI estimation errors at the BS. To guarantee the CSI estimation accuracy while minimizing the RF resource cost, a task-based quantization scheme for channel estimation (TQ-CE) is proposed. In the TQ-CE, both the quantized codebook and the post-processing matrix are optimized to minimize the mean square error (MSE) of the channel estimation. Taking the minimum MSE as the target task, the TQ-CE leverages vector quantization (VQ) to generate a codebook, which is designed to reduce the feedback overhead without compromising the precision of the channel estimation. Then, an optimal closed-form solution of the post-processing matrix is derived based on the minimum mean square error (MMSE) criterion. The simulation results demonstrate that the proposed TQ-CE achieved $0.25\mathrm{Mbit}/\mathrm{s}$ and $0.62\mathrm{Mbit}/\mathrm{s}$ higher data rates compared with the conventional scalar quantization-based channel estimation (SQ-CE) schemes and vector quantization-based channel estimation (VQ-CE) schemes, respectively. Moreover, in terms of the feedback overhead, compared with the 18-bit SQ-CE, the 4-bit TQ-CE achieved a 22.2% reduction in uplink bits. Full article

Over the past few years, wireless communication has grown dramatically, and the consumer demand for wireless services has seen a significant jump. One of the main challenges for beyond fifth generation (B5G) networks is the increased capacity of the network. The continuously increasing number of network users and the limited radio spectrum in wireless technologies have led to severe congestion in communication channels. This issue leads to traffic congestion at base stations and introduces interference in the network, thereby degrading system capability and quality of service. Interference reduction has thus become a major design challenge in wireless communication systems. This review paper comprehensively explores interference management (IM) strategies in B5G networks. We critically analyze and summarize existing research on interference issues related to device-to-device communication, heterogeneous networks, inter-cell interference, and artificial intelligence (AI)-based frameworks. The paper reviews a wide range of methodologies, highlights the strengths and limitations of state-of-the-art approaches, and discusses standardized techniques such as power control, resource allocation, spectrum separation and mode selection, carrier aggregation, load balancing and cell range expansion, enhanced inter-cell interference coordination, coordinated scheduling and beamforming, coordinated multipoint, and AI-based interference prediction methods. A structured taxonomy and comparative summary are introduced to help categorize these techniques. Several related works based on their methodologies, shortcomings, and future directions have been critically reviewed. In addition, the paper identifies open research challenges and outlines key trends that are shaping future B5G IM systems. A comparative visualization is also provided to highlight dominant and underexplored optimization objectives across IM domains. This review serves as a valuable reference for researchers aiming to understand and evaluate current and emerging solutions for interference mitigation in B5G wireless systems. Full article

This paper aims to facilitate the integration of integrated sensing and communication (ISAC) and symbiotic radio (SR), which studies a reconfigurable intelligent surface (RIS)-assisted ISAC-SR system in single-user and multi-user scenarios. In the ISAC-SR system, a base station (BS) transmits the downlink signal to the user while sensing multiple targets. The RIS reflects the BS signal by adjusting its reflection coefficient and embeds its data for user transmission. We aim to maximize the communication rate of RIS by optimizing the transmit beamformers and RIS phase shift matrix while meeting the minimum quality of service (QoS) requirement for BS data transmission and targets sensing. Due to the non-convexity of the formulated problem, in the single-user case, we develop an alternating optimization (AO) algorithm using a semidefinite relaxation (SDR) and the Dinkelbach method to transform it into a convex problem. In the multi-user case, we leverage SDR and successive convex approximation (SCA) to obtain a suboptimal solution and prove that a rank-one solution is guaranteed. Numerical results validate the effectiveness of our proposed schemes. Full article

While speakers of German have adopted many loanwords from other languages throughout history, recent diversification of language use in Germany is mainly driven by the global mobility of English. Previous research has therefore focused on various domains in which English linguistic resources are used, particularly in traditional media and social media communication. Furthermore, many studies on social media communication have also examined English language internet memes more broadly. Despite this plethora of research, little attention has been paid to how English is used in internet memes and reels produced by professional journalists in Germany. Playing a significant role in communication amongst young people, internet memes and reels are used by many German youth media organisations. In particular for youth radio stations in Germany, which have become multimedia outlets, online communication via Instagram is vital for their audience interaction. This paper examines the use of English linguistic resources in a professionally produced Instagram corpus of internet meme and reel captions produced by journalists working for one of the largest youth radio stations in Germany. Data for the analysis of Instagram content were collected as part of the larger ethnographic research project CIDoRA (funded by the European Union). For this project, a mixed methods approach was applied. Methods of data collection and analysis include linguistic ethnography both at the youth radio station and on the station’s Instagram profile page, informal interviews and 20 semi-structured interviews with journalists, and a quantitative and qualitative analysis of 980 meme and reel captions produced for the station’s Instagram profile. Since the youth radio station’s Instagram profile functions as a means of the station’s online self-advertisement, the analysis of this article also draws on a previous study by the researcher. This study analysed possible facilitating factors for the use of catachrestic and non-catachrestic anglicisms in radio station imaging (radio self-advertisement) of six German adult contemporary radio stations. The article therefore includes an analysis of the possible facilitating factors lexical field, brevity of expression, diachronic development of the pragmatic value of lexical items and semantic reasons for the use of English in Instagram content. It thereby explores the differences in anglicism use between these two media formats (radio broadcasting and social media communication) and whether possible facilitating factors for the use of English in adult contemporary radio station imaging are also facilitating factors for the use of English in meme and reel captions produced by the youth radio station. Full article

Space-to-ground laser communication (SGLC) offers a paradigm-shifting solution to overcome the bandwidth constraints of radio frequency systems by leveraging laser beams for ultra-high data throughput, although its link availability probability is significantly affected by atmospheric conditions such as cloud cover. Existing ground station (GS) placement methods decouple site selection from downlink scheduling, failing to effectively quantify the data throughput of candidate sites. This study proposes a data throughput-driven joint optimization framework that integrates downlink scheduling into the site selection model for the first time. Additionally, the site selection model also incorporates equipment cost constraints and service capacity limitations by introducing an integer variable Q to characterize the deployment scale of laser communication terminals (LCTs) at each GS. Through auxiliary variable linearization techniques, the site selection problem is transformed into a tractable integer linear programming (ILP) formulation. A branch-and-bound algorithm is proposed to achieve global optimal solution search. Numerical results demonstrate that the proposed approach improves data throughput compared to the existing method. Full article

The Internet of Underwater Things (IoUT) has attracted significant attention from researchers due to the fact that seventy percent of the Earth’s surface is covered by water. Reliable underwater communication is the enabler of IoUT. Different carriers, such as electromagnetic waves, sound, and light, are used to transmit data through the water. Among these, optical waves are considered promising due to their high data rates and relatively good bandwidth efficiency, as water becomes transparent to light in the visible spectrum (400–700 nm). However, limitations such as link range, path loss, and turbulence lead to low power and, consequently, a low signal-to-noise ratio (SNR) at the receiver. In this article, we present the design of a smart transceiver for bidirectional communication. The system adapts the divergence angle of the optical beam from the transmitter based on the power of the signal received. This paper details the real-time data transmission process, where the transmitting station consists of a light fidelity (Li-Fi) transmitter with a 470 nm blue-light-emitting diode (LED) and a software-defined radio (SDR) for underwater optical communication. The receiving station is equipped with a Li-Fi receiver, which includes a photodetector with a wide field of view and an SDR. Furthermore, we use pulse position modulation (PPM), which demonstrates promising results for real-time transmission. A key innovation of this paper is the integration of the Li-Fi system with the SDR, while the system adapts dynamically using a servo motor and an Arduino microcontroller assembly. The experimental results show that this approach not only increases throughput but also enhances the robustness and efficiency of the system. Full article

Among the several usages of unmanned aerial vehicles (UAVs), a wireless relay system is one of the most promising applications. Specifically, a small fixed-wing UAV is suitable to establish the system promptly. In the system, an antenna pointing control system directs an onboard antenna to a ground station in order to form and maintain a communication link between the UAV and the ground station. In this paper, we propose a sensor system to detect the direction of the ground station from the UAV by using color marker patterns for the antenna pointing control system. The sensor detects the difference between the antenna pointing direction and the ground station direction. The sensor is characterized by the usage of both the color information of multiple color markers and color marker pattern matching. These enable the detection of distant, low-resolution markers, a high accuracy of marker detection, and robust marker detection against motion blur. In this paper, we describe the detailed algorithm of the sensor, and its performance is evaluated by using the prototype sensor system. Experimental performance evaluation results showed that the proposed method had a minimum detectable drawing size of 10.2 pixels, a motion blur tolerance of 0.0175, and a detection accuracy error of less than 0.12 deg. This performance indicates that the method has a minimum detectable draw size that is half that of the ArUco marker (a common AR marker), is 15.9 times more tolerant of motion blur than the ArUco marker, and has a detection accuracy error twice that of the ArUco marker. The color markers in the proposed method can be placed farther away or be smaller in size than ArUco markers, and they can be detected by the onboard camera even if the aircraft’s attitude changes significantly. The proposed method using color marker patterns has the potential to improve the operational flexibility of radio relay systems utilizing UAVs and is expected to be further developed in the future. Full article

In disaster scenarios, e.g., earthquakes, tsunamis, and wildfires, communication infrastructure often becomes severely damaged. To rapidly restore damaged communication systems, we propose a UAV-based mobile base station equipped with Public Safety LTE (PS-LTE) technology to provide standalone communication capabilities. The proposed system includes PS-LTE functionalities, mission-critical push-to-talk, proximity-based services, and isolated E-UTRAN operation to ensure the reliable and secure communication for emergency services. We provide a simulation result to achieve the radio coverage of mobile base station. By using this radio coverage, we find an appropriate location of the end device for performing the outdoor experiments. We develop a prototype of a proposed mobile base station and test its operation in an outdoor environment. The experimental results provide a sufficient data rate to make an independent mobile base station to restore communication infrastructure in areas that experienced environmental disasters. This prototype and experimental results offer a significant step forward in creating agile and efficient communication solutions for emergency scenarios. Full article

As the automotive industry moves toward fully autonomous driving, the goal is to enable vehicles to operate safely without human control in all environments. Implementing Vehicle-to-Everything (V2X) communications in highway environments poses considerable challenges. Several critical services have strict network performance requirements as they deal with safety features. Existing fifth-generation (5G) base station schedulers do not discriminate among critical and non-critical automated driving functions. Therefore, in cases of increased traffic load, there is a significant drop in their performance, and, consequently, increased risk for accidents. Our paper discusses these issues and provides an adaptive scheduler called SOVANET+. The new scheduler acknowledges the Radio Access Network (RAN) load, and the requirements of critical, automated driving applications, together with channel quality, and optimizes the allocation of resources to critical services. The performance of SOVANET+ is evaluated through extensive simulations in the highway environment, an area less examined than urban scenarios. Results indicate that the adoption of SOVANET+ presents clear advantages to critical services compared to existing solutions. Full article

Energy harvesting (EH) from radio frequency (RF) signals provides a promising approach for supplying sustainable and convenient energy to low-power Internet of Things (IoT) devices. In this work, we investigate short-packet communications in a full-duplex (FD) relay system, where RF signals from a source are utilized to power an energy-constrained relay through the time switching protocol. Specifically, hardware impairments in each node and residual self-interference caused by FD are jointly considered. To ensure reliable transmission, two antennas are symmetrically arranged according to the position of the relay station, both of which are used for energy harvesting. Furthermore, we explored two practical schemes based on symmetric channel correlation, i.e., an independent channel for energy harvesting and an identical channel for energy harvesting. For both scenarios, we derive closed-form approximations for the overall average block error rate (BLER) and effective throughput. The validity of our analysis is confirmed through computer simulations, demonstrating that the proposed scheme enhances the reliability and throughput of the system compared with the existing scheme in the literature at low transmission rates and transmit signal-to-noise-ratios (SNRs). Full article

Wireless Sensor Networks are formed by tiny, self-contained, battery-powered computers with radio links that can sense their surroundings for events of interest and store and process the sensed data. Sensor nodes wirelessly communicate with each other to relay information to a central base station. Energy consumption is the most critical parameter in Wireless Sensor Networks (WSNs). Network lifespan is directly influenced by the energy consumption of the sensor nodes. All sensors in the network send and receive data from the base station (BS) using different routing protocols and algorithms. These routing protocols use two main types of clustering: hierarchical clustering and flat clustering. Consequently, effective clustering within Wireless Sensor Network (WSN) protocols is essential for establishing secure connections among nodes, ensuring a stable network lifetime. This paper introduces a novel approach to improve energy efficiency, reduce the length of network connections, and increase network lifetime in heterogeneous Wireless Sensor Networks by employing the K-Nearest Neighbours (KNN) algorithm to optimise node selection and clustering mechanisms for four protocols: Low-Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP), Threshold-sensitive Energy Efficient sensor Network (TEEN), and Distributed Energy-efficient Clustering (DEC). Simulation results obtained using MATLAB (R2024b) demonstrate the efficacy of the proposed K-Nearest Neighbours algorithm, revealing that the modified protocols achieve shorter distances between cluster heads and nodes, reduced energy consumption, and improved network lifetime compared to the original protocols. The proposed KNN-based approach enhances the network’s operational efficiency and security, offering a robust solution for energy management in WSNs. Full article

Unmanned aerial vehicles (UAVs) significantly shape the evolution of 5G and 6G technologies in India, particularly in reconfiguring communication networks. Through their deployment as base stations or relays, these aerial vehicles substantially enhance communication performance and extend network coverage in areas characterized by high demand and challenging topographies. Accurate modelling of the UAV-to-ground channel is imperative for gaining valuable insights into UAV-assisted communication systems, particularly within India’s rapidly expanding metropolitan cities and their diverse topographical complexities. This study proposes an approach to model low-altitude channels in urban areas, offering specific scenarios and tailored solutions to facilitate radio frequency (RF) planning for Indian metropolitan cities. The proposed model leverages the International Telecommunication Union recommendation (ITU-R) for city mapping and utilizes frequency ranges from 1.8 to 6 GHz and altitudes up to 500 m to comprehensively model both line-of-sight (LoS) and non-line-of-sight (NLoS) communications. It employs the uniform theory of diffraction to calculate the additional path loss for non-line-of-sight (NLoS) communication for both vertical and horizontal polarizations. The normal distribution for additional shadowing loss is discerned from simulation results. This study outlined the approach to derive a comprehensive statistical channel model based on the elevation angle and evaluate model parameters at various frequencies and altitudes for both vertical and horizontal polarization. The model was subsequently compared with existing models for validation, showing close alignment. The ease of implementation and practical application of this proposed model render it an invaluable tool for planning and simulating mobile networks in urban areas, thus facilitating the seamless integration of advanced communication technologies in India. Full article

This paper presents the development and outcomes of a cost-effective satellite ground station designed as a learning tool for satellite communication and wireless communication education. The study investigates accessible satellites and the methods for accessing them. The developed ground station has the capability to access satellites in the V, U, and L frequency bands, allowing it to receive a variety of satellite data. This includes full-disk meteorological images, high-resolution multispectral images, and scientific data from payloads of satellites in both low Earth orbit (LEO) and geostationary orbit (GEO). The ground station demonstrates capabilities similar to those of large organizations but at a significantly lower cost. This is achieved through a process of identifying educational requirements and optimizing the system for cost-efficiency. This paper presents the design demonstration, actual construction of the ground station, and results. Additionally, it compiles characteristics from real signal reception experiences from various satellites. Full article