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Violence, a pervasive societal concern, demands innovative approaches for its early detection and prevention. This review paper explores the intersection of violence detection and wireless fidelity (Wi-Fi), alongside fifth-generation (5G) and sixth-generation (6G) mobile technologies. Wi-Fi sensing, initially employed for human activity detection, has also demonstrated versatility across a number of other important applications. The significance of leveraging Wi-Fi sensing for violence detection is investigated, underscoring its ability to enhance security protocols and minimise response time. Moreover, through the development and use of machine learning algorithms to analyse and interpret intricate channel state information (CSI) features, the accuracy of violence detection can be improved. Furthermore, this investigation delves into the rapidly developing domain of mobile sensing, examining its contribution to the advancement of violence detection functionalities. The potential convergence of 5G and forthcoming 6G sensing technologies increases the effectiveness of violence detection. Through an analysis of Wi-Fi and mobile sensing technologies, this review paper highlights the transformative capacity that their integration may have on approaches to violence prevention and response. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is what we have as a great breakthrough in the 5G network. Although the 5G network can support several Internet of Everything (IoE) services, 6G is the network to fully support that. This paper is a survey research presenting the 5G and IoT technology and the challenges coming, with the 6G network being the new alternative network coming to solve these issues and limitations we are facing with 5G. A reference to the Control Plane and User Plane Separation (CUPS) is made with IPv4 and IPv6, addressing which is the foundation of the network slicing for the 5G core network. In comparison to other related papers, we provide in-depth information on how the IoT is going to affect our lives and how this technology is handled as the IoE in the 6G network. Finally, a full reference is made to the 6G network, with its challenges compared to the 5G network. [ABSTRACT FROM AUTHOR]

Passive radar detection emerges as a pivotal method for environmental perception and target detection within radar applications. Through leveraging its advantages, including minimal electromagnetic pollution and efficient spectrum utilization, passive radar methodologies have garnered increasing interest. In recent years, there has been an increasing selection of passive radar signal sources, and the emerging 5G has the characteristics of a high-frequency band, high bandwidth, and a large number of base stations, which give it significant advantages for use in passive radar. Therefore, in this paper, we introduce a passive radar target detection method based on 5G signals and design a rotating target speed measurement experiment. In the experiment, this paper validated the method of detecting rotating targets using 5G signals and evaluated the measurement accuracy, providing a research foundation for passive radar target detection using 5G signals and detecting rotating targets such as drone rotors. [ABSTRACT FROM AUTHOR]

Deploying 5G in new and diverse use cases, such as Industry 4.0 and factory automation, requires 5G systems to harmonize with the communication technologies used in these industries. To this end, 3GPP Release 16 and Release 17 have made significant progress in integrating 5G systems with the IEEE 802.1 working group specifications on Time-Sensitive Networking (TSN). This paper explains a method and architecture for supporting TSN over a wireless channel in a 5G network that adds the TSN synchronization function in a Small Cell gNB implementing the TSN Translator function (SC-TT). This TSN-capable small cell provides TSN over the wireless network to synchronize UEs with the Grand Master (GM) using the physical layer signal of the 5G radio frame and the transmission of the GM reference time to provide high-precision synchronization. This paper explores the pivotal role of a Slot Indicator Signal in enhancing synchronization precision, ensuring that the UE-GM synchronization occurs within an exceptionally narrow timeframe as small as 10 ns. [ABSTRACT FROM AUTHOR]

In this paper, a diamond-shaped broadband high-gain microstrip patch antenna based on a folded floor structure is proposed. The overall dimensions of the antenna are 108 mm×100 mm×25 mm. Additionally, it contains a radiating microstrip patch, a folded ground plane, and a capacitive feed strip. The broadening of the antenna's operating band is achieved by enhancing the microstrip radiating patch and capacitive feed band. The original rectangular structure was transformed into a rhombic structure, enabling the radiating patch to absorb the current more effectively and achieve a better impedance match for the antenna operating around 5 GHz. The radiation performance of the antenna is maximized by utilizing the folded floor structure. Measured results show that the impedance bandwidth of the antenna is about 61.5% (2.84 GHz-5.36 GHz), covering 5G dual bands. Meanwhile, the peak gain reaches 12.6 dBi, and the average gain reaches 10.7 dBi. [ABSTRACT FROM AUTHOR]

In vehicular communications, channel estimation is a complex problem due to the joint time–frequency selectivity of wireless propagation channels. To this end, several signal processing techniques as well as approaches based on neural networks have been proposed to address this issue. Due to the highly dynamic and random nature of vehicular communication environments, precise characterization of temporal correlation across a received data sequence can enable more accurate channel estimation. This paper proposes a new pilot constellation scheme in combination with a small feed‐forward neural network to improve the accuracy of channel estimation in V2X systems while keeping low the implementation complexity. The performance is evaluated in typical vehicular channels using simulated BER curves, and it is found superior to traditional channel estimation methods and state‐of‐the‐art neural‐network‐based implementations such as feed‐forward and super‐resolution. It is illustrated that the improvement becomes pronounced for small subcarrier spacings (or low 5G numerologies); hence, this paper contributes to the development of more reliable mobile services across rapidly varying vehicular communication channels with rich multi‐path interference. [ABSTRACT FROM AUTHOR]

Radio Determination Satellite Service (RDSS) is a characteristic service of BeiDou, which can provide users with short message communication services. Since the working frequency of an RDSS system is close to that of a 5G system, the RDSS system is very susceptible to interference from 5G out-of-band radiation. This paper analyzes the compatibility of 5G interference with an RDSS system from the perspective of the signal and the system. Firstly, the compatibility assessment is carried out from the perspective of the signal, the impact of interference on the capture and tracking performance of BeiDou is illustrated, and the safe coexistence distance of the two systems from the perspective of capture probability is obtained from the perspective of the signal. Subsequently, based on the link budget criterion, the interference of 5G base stations and 5G terminals to RDSS receivers under different frequency isolation and the required distance isolation for safe coexistence are analyzed from the system perspective. Finally, from the perspective of civil aviation safety, the aggregate interference is used as an evaluation index to evaluate the interference suffered by the aircraft during takeoff and landing and to obtain the interference suffered by the ground-based 5G base station during the takeoff and landing of the aircraft on different routes and in different 5G propagation environments. The simulation results show that when the airplane is closer to the ground, the ground 5G base stations will cause harmful interference to the RDSS receiver. In this study, the real flight data are combined with the simulation model to obtain the exact influence range of 5G interference on the RDSS system under different viewpoints. [ABSTRACT FROM AUTHOR]

Establishing a national comprehensive PNT (Positioning, Navigation, and Timing) system has become a consensus among major countries worldwide. As a crucial component in completing the entire PNT system, the 5G NR (new radio) time service signal plays a vital role. This paper proposes a 5G NR time service signal that uses a spread spectrum system, shares the 5G signal frequency band, but does not occupy the bandwidth of the 5G communication signal. This timing service signal has relatively low power, making it appear "submerged" within the power of the 5G communication signal. The spread spectrum code for this timing signal employs the chaotic orthogonal composite sequence proposed in this paper. Compared to traditional spread spectrum sequences, this sequence offers better security than m-sequences, improved autocorrelation than Walsh sequences, and an effective suppression of the short-period characteristics exhibited when the Skew Tent-Map chaotic sequence takes special values. This paper simulates the capture of the 5G NR time service signal in an environment with a signal-to-noise ratio of 10 dB using an FFT-based parallel code phase search algorithm, successfully capturing the 5G NR time service signal and verifying the feasibility of the proposed chaotic orthogonal composite sequence as a spread spectrum code. [ABSTRACT FROM AUTHOR]

This paper presents the algorithmic framework for a multimodal hearing aid (HA) prototype designed on a Field Programmable Gate Array (FPGA), specifically the RFSOC4*2 AMD FPGA, and evaluates the transmitter performance through simulation studies. The proposed architecture integrates audio and video inputs, processes them using advanced algorithms, and employs the 5G New Radio (NR) communication protocol for uploading the processed signal to the cloud. The core transmission utilizes Orthogonal Frequency Division Multiplexing (OFDM), an algorithm that effectively multiplexes the processed signals onto various orthogonal frequencies, enhancing bandwidth efficiency and reducing interference. The design is divided into different modules such as Sound reference signal (SRS), demodulation reference signal (DMRS), physical broadcast channel (PBCH), and physical uplink shared channel (PUSCH). The modulation algorithm has been optimized for FPGA parallel processing capabilities, making it better suited for the hearing aid requirements for low latency. The optimized algorithm achieves a transmission time of only 4.789 ms and uses fewer hardware resources, enhancing performance in a cost-effective and energy-efficient manner. [ABSTRACT FROM AUTHOR]

This paper presents a compact 8×8 multiple-input-multiple-output (MIMO) antenna system designed to operate across two wide frequency bands suitable for fifth-generation (5G) mobile network and wireless local area network (WLAN) applications. Each antenna element comprises a radiator, a feeding line, and a defected ground plane. Each radiator consists of a first L-shaped radiator (FLR), a second L-shaped radiator (SLR), and an extra radiator (ER). To enhance the isolation, a defected ground structure (DGS) is employed between the antenna elements. The presented antenna operates across three frequency bands, namely, 3.5 GHz (3.3 GHz-3.8 GHz) and 4.9 GHz (4.8 GHz-5 GHz) 5G frequency bands, and 5.7 GHz (5.15 GHz-5.85 GHz) WLAN frequency band, exhibiting excellent isolation, surpassing 15 dB in both lower and higher frequency bands. The overall efficiency exceeds 58%, with an envelope correlation coefficient (ECC) value below 0.125. The simulation and measurement results are in good agreement. [ABSTRACT FROM AUTHOR]

The rapid advancements in automotive technology and the emergence of next-generation networks such as 5G and 6G are laying the foundation for the internet of vehicles (IoV), a revolutionary concept to transform transportation systems. The convergence of artificial intelligence (AI) and connected vehicles IoV is driving a paradigm shift in the transportation sector, especially in the dynamic framework of 5G and future 6G networks. This survey paper provides a thorough survey of the evolving AI-based IoV security landscape. We explore key areas of 5G/6G networks, focusing on the complex interplay of machine learning (ML) and deep learning (DL) in enhancing vehicle-to-everything (V2X) security and connected vehicles. Addressing the unique challenges of 6G, this paper outlines future directions for improving security and highlights open research issues. This comprehensive survey, which aims to provide information and guidance to both researchers and practitioners, contributes to a detailed understanding of the security issues associated with connected vehicles in the emerging 6G era. [ABSTRACT FROM AUTHOR]

In everyday life, 5G-based localization technology is commonly used, but non-line-of-sight (NLOS) environments can block the propagation of the localization signal, thus preventing localization. In order to solve this problem, this paper proposes a reconfigurable intelligent surface non-line-of-sight time difference of arrival (TDOA) localization (RNTL) algorithm. Firstly, a model of a reflective-surface-based intelligent localization (RBP) system is constructed, which utilizes multiple RISs deployed in the air to reflect signals. Secondly, in order to reduce the localization error, this paper establishes the optimization problem of minimizing the distance between each estimated coordinate and the actual coordinate and solves it via the piecewise linear chaotic map–gray wolf optimization algorithm (PWLCM-GWO). Finally, the simulation results show that the RNTL algorithm significantly outperforms the traditional gray wolf optimization and particle swarm optimization algorithms in different signal-to-noise ratios, and the localization errors are reduced by 46% and 53.5%, respectively. [ABSTRACT FROM AUTHOR]

Intrusion Detection Systems (IDSs) are an important tool to mitigate cybersecurity threats in the ICT infrastructures. Preferable properties of the IDSs are the optimization of the attack detection accuracy and the minimization of the computing resources and time. A signification portion of IDSs presented in the research literature is based on Machine Learning (ML) and Deep Learning (DL) elements, but they may be prone to adversarial attacks, which may undermine the overall performance of the IDS algorithm. This paper proposes a novel IDS focused on the detection of cybersecurity attacks in 5G networks, which addresses in a simple but effective way two specific adversarial attacks: (1) tampering of the labeled set used to train the ML algorithm, (2) modification of the features in the training data set. The approach is based on the combination of two algorithms, which have been introduced recently in the research literature. The first algorithm is the Extremely Randomized Tree (ERT) algorithm, which enhances the capability of Decision Tree (DT) and Random Forest (RF) algorithms to perform classification in data sets, which are unbalanced and of large size as IDS data sets usually are (legitimate traffic messages are more numerous than attack related messages). The second algorithm is the recently introduced Infinite Feature Selection algorithm, which is used to optimize the choice of the hyper-parameter defined in the approach and improve the overall computing efficiency. The result of the application of the proposed approach on a recently published 5G IDS data set proves its robustness against adversarial attacks with different degrees of severity calculated as the percentage of the tampered data set samples. [ABSTRACT FROM AUTHOR]

The rise of 5G technology has brought with it a surge in diverse services with demanding and varying requirements. Network fragmentation has emerged as a critical technique to address this challenge, enabling the creation of virtual network segments on a shared infrastructure, allowing for efficient resource utilization and improved performance. This paper investigates the potential of network fragmentation, combined with optimized resource allocation, to enhance the performance of 5G core networks. A novel framework that integrates these two techniques is proposed. The former takes into account factors, such as network traffic patterns, service requirements, and resource availability. The framework aims to optimize network performance metrics, namely throughput, latency, and resource utilization. The experimental results demonstrate the effectiveness of the proposed framework, showcasing a significant improvement in overall network performance, paving thus the way for efficient and robust 5G service delivery. [ABSTRACT FROM AUTHOR]

Network load in mobile networks is continuously growing, putting pressure on mobile operators to deliver target network performance and user experience. This paper focuses on network capacity improvement through increased spectral efficiency, which can be achieved with overhead reduction by optimizing the demodulation reference signal (DM-RS) configuration, which is one of the channels/reference signals with the largest contribution to overhead. In a high-speed scenario, the Doppler effect noticeably influences the temporal nature of the channel such that a channel interpolation process is required within a slot. However, increasing the number of symbols used for DM-RS has a negative impact on capacity. The Doppler effect was analyzed for various 5G NR configurations of operating frequency and subcarrier spacing (SCS), and various use cases were considered using user equipment (UE) speed as the main parameter. For suitable use cases, the DM-RS configuration was optimized in networks with live traffic. The impact of the configuration change on 5G/NR spectral efficiency, user experience and link adaptation performance was assessed through a deep-dive analysis of active measurements, available performance Management (PM) counters and key performance indicators. An optimized DM-RS configuration is proposed, and it is demonstrated to achieve gains of 5–15%, depending on the metric used, use case analyzed, network load, traffic mix and other relevant network characteristics such as topology and clutter type. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) offer comprehensive position, navigation, and timing (PNT) estimates worldwide. Given the growing demand for reliable location awareness in both indoor and outdoor contexts, the advent of fifth-generation mobile communication technology (5G) has enabled expansive coverage and precise positioning services. However, the power received by the signal of interest (SOI) at terminals is notably low. This can lead to significant jamming, whether intentional or unintentional, which can adversely affect positioning receivers. The diagnosis of jamming types, such as classification, assists receivers in spectrum sensing and choosing effective mitigation strategies. Traditional jamming diagnosis methodologies predominantly depend on the expertise of classification experts, often demonstrating a lack of adaptability for diverse tasks. Recently, researchers have begun utilizing convolutional neural networks to re-conceptualize a jamming diagnosis as an image classification issue, thereby augmenting recognition performance. However, in real-world scenarios, the assumptions of independent and homogeneous distributions are frequently violated. This discrepancy between the source and target distributions frequently leads to subpar model performance on the test set or an inability to procure usable evaluation samples during training. In this paper, we introduce LJCD-Net, a deep adversarial migration-based cross-domain jamming generalization diagnostic network. LJCD-Net capitalizes on a fully labeled source domain and multiple unlabeled auxiliary domains to generate shared feature representations with generalization capabilities. Initially, our paper proposes an uncertainty-guided auxiliary domain labeling weighting strategy, which estimates the multi-domain sample uncertainty to re-weight the classification loss and specify the gradient optimization direction. Subsequently, from a probabilistic distribution standpoint, the spatial constraint imposed on the cross-domain global jamming time-frequency feature distribution facilitates the optimization of collaborative objectives. These objectives include minimizing both the source domain classification loss and auxiliary domain classification loss, as well as optimizing the inter-domain marginal probability and conditional probability distribution. Experimental results demonstrate that LJCD-Net enhances the recognition accuracy and confidence compared to five other diagnostic methods. [ABSTRACT FROM AUTHOR]

In distributed edge storage, data storage data is allocated to network edge devices to achieve low latency, high security, and flexibility. However, traditional systems for distributed edge storage only consider individual factors, such as node capacity, while overlooking the network status and the load states of the storage nodes, thereby impacting the system's read and write performance. Moreover, these systems exhibit inadequate scalability in widely adopted wireless terminal application scenarios. To overcome these challenges, this paper introduces a software-defined edge storage model and a distributed edge storage architecture grounded in software-defined networking (SDN) and the Server Message Block (SMB) protocol. A data storage node selection and distribution algorithm is formulated based on a maldistributed decision model that comprehensively considers the network and storage node load states. A system prototype is implemented in combination with 5G wireless communication technology. The experimental results demonstrate that, in comparison to conventional distributed edge storage systems, the proposed wireless distributed edge storage system exhibits significantly enhanced performance under high load conditions, demonstrating superior scalability and adaptability. This approach effectively addresses the scalability limitation, rendering it suitable for edge scenarios in mobile applications and reducing hardware deployment costs. [ABSTRACT FROM AUTHOR]

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The paper presents an experimental security assessment within two widely used open-source 5G projects, namely Open5GS and OAI (Open-Air Interface). The examination concentrates on two network functions (NFs) that are externally exposed within the core network architecture, i.e., the Access and Mobility Management Function (AMF) and the Network Repository Function/Network Exposure Function (NRF/NEF) of the Service-Based Architecture (SBA). Focusing on the Service-Based Interface (SBI) of these exposed NFs, the analysis not only identifies potential security gaps but also underscores the crucial role of Mobile Network Operators (MNOs) in implementing robust security measures. Furthermore, given the shift towards Network Function Virtualization (NFV), this paper emphasizes the importance of secure development practices to enhance the integrity of 5G network functions. In essence, this paper underscores the significance of scrutinizing security vulnerabilities in open-source 5G projects, particularly within the core network's SBI and externally exposed NFs. The research outcomes provide valuable insights for MNOs, enabling them to establish effective security measures and promote secure development practices to safeguard the integrity of 5G network functions. Additionally, the empirical investigation aids in identifying potential vulnerabilities in open-source 5G projects, paving the way for future enhancements and standard releases. [ABSTRACT FROM AUTHOR]

The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future. [ABSTRACT FROM AUTHOR]

Positioning based on wireless signals such as mobile communication networks has become an important means to provide high-precision location services in environments where satellite signals are blocked. In complex environments such as indoors and underground, wireless signal propagation is obstructed and non-line-of-sight (NLOS) phenomena appear due to serious occlusion and reflection. The time delay caused by NLOS effects has little impact on communication system but can significantly increase positioning errors in positioning systems. Therefore, the effective suppression of NLOS errors is crucial to improving 5G positioning accuracy. To address the insufficient feature extraction of existing NLOS error suppression methods, the neglect of residual NLOS measurement errors, and poor stability of position estimation results, this paper innovatively proposes an NLOS mitigation and location estimation method for 5G positioning terminals. Simulation and experimental test results demonstrate that the proposed method outperforms the comparative methods both theoretically and practically, achieving an average positioning accuracy of 1.85 m in complex indoor NLOS environments. The method proposed in this paper provides a new strategy for NLOS error suppression in indoor 5G positioning, which can significantly contribute to high-precision location services based on commercial 5G networks. [ABSTRACT FROM AUTHOR]

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beamforming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beamforming technologies and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beamforming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future technology landscapes while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beamforming, and dual radar communication technologies. [ABSTRACT FROM AUTHOR]

Many emerging applications, such as factory automation, electric power distribution, and intelligent transportation systems, require multicast Ultra-Reliable Low-Latency Communications (mURLLC). Since 3GPP Release 17, 5G systems natively support multicast functionality, including multicast Hybrid Automatic Repeat Request and various feedback schemes. Although these features can be promising for mURLLC, the specifications and existing studies fall short in offering guidance on their efficient usage. This paper presents the first comprehensive system-level evaluation of mURLLC, leveraging insights from 3GPP specifications. It points out (i) how mURLLC differs from traditional multicast broadband wireless communications, and (ii) which approaches to provide mURLLC require changing the paradigm compared with the existing solutions. Finally, the paper provides recommendations on how to satisfy strict mURLLC requirements efficiently, i.e., with low channel resource consumption, which increases the capacity of 5G systems for mURLLC. Simulation results show that proper configuration of multicast mechanisms and the corresponding algorithms for mURLLC traffic can reduce resource consumption up to three times compared to the baseline solutions proposed for broadband multicast traffic, which significantly increases the system capacity. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) technology is one of the keys to the Industrial Revolution known as Industry 4.0 as it provides faster connectivity and allows a greater number of devices to be connected simultaneously. In the transport sector, newly produced vehicles are equipped with various sensors and applications to help drivers perform safe maneuvers. However, moving from semiautonomous to fully autonomous vehicles to cooperating systems remains a major challenge. Many researchers have focused on artificial intelligence (AI) techniques and the ability to share information to achieve this cooperative behavior. This information can be made up of different data, which can be obtained from different sensors such as laser imaging detection and ranging (LiDAR), radar, camera, global positioning system (GPS), or data related to the current speed, acceleration, or position. The combination of the different shared data is performed depending on the approach of each navigation algorithm. This data fusion will allow a better understanding of the environment but will overload the network, as the traffic generated will be massive. Therefore, this paper addresses the challenge of achieving this cooperation between vehicles from the point of view of network requirements and computational capacity. In addition, this study contributes to advancing theory into real-world practice by examining the performance of cooperative navigation algorithms in the midst of the migration of computational resources from onboard vehicle equipment to the cloud. In particular, it investigates the transition from a cooperative navigation algorithm based on a decentralized architecture to a semidecentralized one as computationally demanding processes previously performed onboard are performed in the cloud. Additionally, the paper discusses the indispensable role of 5G in fulfilling the escalating demands for high throughput and low latency in these services, particularly as the number of vehicles increases. The results of the tests show that the AI acting alone cannot achieve optimal performance, even using 100% of the computational capacity of the onboard equipment in the vehicle. However, a system that integrates 5G and AI-based joint decisions can achieve better performance, reduce the computational resources consumed in the vehicle, and increase the efficiency of collaborative choices by up to 83.3%. [ABSTRACT FROM AUTHOR]

The beyond 5G millimeter-wave cellular network system is expected to provide high-quality service in indoor areas. Due to the high density of obstacles, cooperative communication techniques are employed to improve the user's desired signal power by finding more than one appropriate station to serve that user. While the conventional system utilizes additional equipment such as Reconfigurable Intelligent Surfaces (RIS) and relays to enable cooperative features, the paper introduces a new network paradigm that utilizes the second nearest Base Station (BS) of the typical user as the Decode and Forward (DF) relay. Thus, depending on the success of decoding the message from the user's serving BS or the second nearest BS, the typical user can work with or without assistance from the relay, whose operation follows the discipline of the power-domain NOMA technique. In the case of relay assistance, the Maximum Ratio Combining technique is utilized by the typical user to combine the desired signals. To examine the performance of the proposed system, the Nakagamim and the newly developed path loss model, which considers the density of walls and their properties, are adopted to derive the coverage probability of the user with and without relay assistance. The closedform expressions of this performance metric are derived using Gauss quadrature and Welch-Satterthwaite approximation. Through analytical and simulation results, it is seen that the proposed system can improve the user coverage probability by up to 10%. [ABSTRACT FROM AUTHOR]

Network traffic prediction is an important network monitoring method, which is widely used in network resource optimization and anomaly detection. However, with the increasing scale of networks and the rapid development of 5-th generation mobile networks (5G), traditional traffic forecasting methods are no longer applicable. To solve this problem, this paper applies Long Short-Term Memory (LSTM) network, data augmentation, clustering algorithm, model compression, and other technologies, and proposes a Cluster-based Lightweight PREdiction Model (CLPREM), a method for real-time traffic prediction of 5G mobile networks. We have designed unique data processing and classification methods to make CLPREM more robust than traditional neural network models. To demonstrate the effectiveness of the method, we designed and conducted experiments in a variety of settings. Experimental results confirm that CLPREM can obtain higher accuracy than traditional prediction schemes with less time cost. To address the occasional anomaly prediction issue in CLPREM, we propose a preprocessing method that minimally impacts time overhead. This approach not only enhances the accuracy of CLPREM but also effectively resolves the real-time traffic prediction challenge in 5G mobile networks. [ABSTRACT FROM AUTHOR]

As mobile communications transform, 5G technology can potentially change many industries and businesses. The change will have a great influence across many fields, such as the automotive, healthcare, and manufacturing sectors. This paper aims to review the existing applications of blockchain technology in providing 5G network security and identify new possibilities for such security solutions. We consider different aspects of blockchain in 5G, particularly data transmission, access control, and applications including vertical industry-oriented applications and specific solutions supporting such sectors of economic activity. The paper briefly describes modern technologies in 5G networks and introduces blockchain's properties and different aspects of using such technology in practical applications. It also presents access control management with blockchain applied in 5G and related problems, reviews other blockchain-enforced network technologies, and shows how blockchain can help in services dedicated to vertical industries. Finally, it presents our vision of new blockchain applications in modern 5G networks and beyond. The new-generation networks use two fundamental technologies, slicing and virtualization, and attackers attempt to execute new types of attacks on them. In the paper, we discuss one of the possible scenarios exhibiting the shortcomings of the slicing technology architecture. We propose using blockchain technology to create new slices and to connect new or existing subscribers to slices in the 5G core network. Blockchain technology should solve these architectural shortcomings. [ABSTRACT FROM AUTHOR]

To enhance the reliability of traditional current protection systems in the evolving landscape of future power grids, this paper proposes a differential protection data synchronization approach that leverages satellite and 5G network timing. This method addresses the risk of inadvertent operation due to 5G communication jitter. It employs the BeiDou satellite system for synchronizing the timing of 5G base stations and terminals. This synchronization extends to the 5G terminal and the protection device, thereby mitigating time deviations caused by air interface delays and reducing the 5G network's end-to-end delay by approximately 4 ms on average. A simulation was conducted to assess the reliability and effectiveness of the proposed method under normal satellite signal conditions. The results indicated a significant improvement in protection accuracy, with the method reducing the protection activation time by approximately 5–7 ms compared to the 5G timing data synchronization method. This advancement offers technical support for the safe and stable operation of new power systems. [ABSTRACT FROM AUTHOR]

This paper presents and discusses the development and deployment of a tour guide robot as part of the 5 g-TOURS EU research project, aimed at developing applications enabled by 5G technology in different use cases. The objective is the development of an autonomous robotic application where intelligence is off-loaded to a remote machine via 5G network, so as to lift most of the computational load from the robot itself. The application uses components that have been widely studied in robotics, (i.e., localization, mapping, planning, interaction). However, the characteristics of the network and interactions with visitors in the wild introduce specific problems which must be taken into account. The paper discusses in detail such problems, summarizing the main results achieved both from the methodologicaland the experimental standpoint, and is completed by the description of the general functional architecture of the whole system, including navigation and operational services. The software implementation is also publicly available. [ABSTRACT FROM AUTHOR]

A multiple-input-multiple-output (MIMO) antenna system with low-profile and small element spacing characteristics is presented in this paper. This antenna contains multiple elements arranged in both E-plane and H-plane configurations. The original strong coupling between the MIMO elements can be suppressed by exciting orthogonal operating modes. To achieve this, a half-wavelength microstrip line and a quarter-wavelength grounded stub are utilized to decouple the H- and E-plane MIMO arrays. A 2 × 2 antenna prototype is fabricated and measured to demonstrate the decoupling concept's feasibility. The measured impedance bandwidth is from 4.78 to 4.81 GHz. Across this band, the isolation is better than 15 dB with extremely small edge-to-edge distances of 0.032λ and 0.026λ in the E- and H-plane, respectively. Featuring the simple decoupling structure, small element spacing, and the capability of extending to a large-scale 2 × N array, the proposed antenna can be used for 5G Internet of Things (IoT) applications operating at the N79 frequency band. [ABSTRACT FROM AUTHOR]

Handoff mechanisms are very important in fifth-generation (5G) mobile networks because of the cellular architecture employed to maximize spectrum utilization. Together with call admission control (CAC) mechanisms, they enable better optimization of bandwidth use. The primary objective of the research presented in this article is to analyze traffic levels, aiming to optimize traffic management and handling. This article considers the two most popular CAC mechanisms: the resource reservation mechanism and the threshold mechanism. It presents an analytical approach to occupancy distribution and blocking probability calculation in 5G mobile networks, incorporating connection handoff and CAC mechanisms for managing multiple traffic streams generated by multi-service sources. Due to the fact that the developed analytical model is an approximate model, its accuracy was also examined. For this purpose, the results of analytical calculations of the blocking probability in a group of 5G cells are compared with the simulation data. This paper is an extended version of our paper published in 17th ConTEL 2023. [ABSTRACT FROM AUTHOR]

Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices' contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol's time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G. [ABSTRACT FROM AUTHOR]

This paper addresses the resource allocation (RA) for ultra‐dense network (UDN), where base stations (BSs) are densely deployed to meet the demands of future wireless communications. However, the design of RA in UDN is challenging, as the RA problem is non‐convex and NP‐hard. Therefore, this paper considers and studies a semi‐distributed resource block (RB) allocation scheme, in order to achieve a well‐balanced trade‐off between performance and complexity. In the context of semi‐distributed RB allocation scheme, the problem can be decomposed into the subproblem of clustering and the subproblem of cluster‐based RB allocation. We first improve the K‐means clustering algorithm by employing the Gaussian modified method, which can significantly decrease the number of iterations for carrying out the K‐means algorithm as well as the failure possibility of clustering. Then, bat algorithm (BA) is introduced to attack the problem of cluster‐based RB allocation. In order to make the original BA applicable to the problem of RB allocation, chaotic sequences are adopted to discretize the initial position of the bats, and simultaneously increase the population diversity of the bats. Furthermore, in order to speed up the convergence of BA, the logarithmic decreasing inertia weight is employed for improving the original BA. Our studies and performance results show that the proposed approaches are capable of achieving a desirable trade‐off between the performance and the implementation complexity. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive overview of microstrip passive components for energy harvesting and 5G applications. The paper covers the structure, fabrication, and performance of various microstrip passive components such as filters, couplers, diplexers, and triplexers. The size and performance of several 5G and energy harvester microstrip passive devices are compared and discussed. The review highlights the importance of these components in enabling efficient energy harvesting and high-speed communication in 5G networks. In addition, the paper discusses the latest advancements in microstrip technology and identifies key research challenges and future directions in this field. Overall, this review serves as a valuable resource for researchers and engineers working on microstrip passive components for energy harvesting and 5G applications. [ABSTRACT FROM AUTHOR]

To study physiological reactions in the brain and skin of higher mammals exposed to chronic radiofrequency radiation, specific absorption ratio (SAR) determination is required and time-consuming numerical methods are used. The paper deals with the estimation of the whole-body specific absorption rate (SAR) in rats chronically exposed to external electromagnetic fields, as well as the development of a laboratory setup simulating the operation of a fifth-generation 5G New Radio base station (with a signal bandwidth of 15 MHz and a carrier frequency of 2.4 GHz). The paper presents a modified method for theoretical SAR estimation for one-sided irradiation and distributed absorption. Mean whole-body SAR values were estimated by the proposed method and numerically modeled with the CST Microwave Studio simulation software 2020package using primitive rat models. Dielectric parameters in the numerical simulation were used from the software library. The IEEE/IEC 62704-1 algorithm was used to investigate SAR in numerical simulations. The theoretical estimates and numerical simulations were compared for different SAR distributions and were found to be qualitatively comparable. The differences between approximate theoretical estimates and numerical simulations are 7% and 10% for distributed and non-distributed absorptions, respectively. The proposed method, which takes into account the decreasing power flux density, can be used to estimate the approximate whole-body SAR during chronic electromagnetic field exposure in rats. [ABSTRACT FROM AUTHOR]

The increasing volumes of data generated by social networking, cloud computing, e-commerce, and online video broadcasting necessitate the implementation of higher data rates. As the current 4G network encounters congestion and potentially struggles to accommodate the substantial data demand, there is a growing interest in millimeter wave (mmWave) technology. The 30-300 GHz mmWave spectrum is characterized by its broad bandwidth and low latencyÍ? it is having many applications in communication domains, also includes 5G cellular. Despite its atmospheric attenuation and non-line-of-sight (NLOS) propagation, the majority of nations have begun to implement mmWave 5G in the band of 28/38 GHz as a result of its reduced path loss exponent, minimal signal spread, and decreased atmospheric attenuation. While the patch antenna (single-element) is a compact and easily transportable choice for mmWave applications, its radiation efficiency, gain, and bandwidth are all subpar. Array antennas have effectively addressed these limitations by exhibiting significant enhancements in bandwidth, gain, and radiation efficiency. It is still limited in the maximum data rates it can accommodate. The rate of data can be increased by a factor of one thousand using Multiple-Input-Multiple-Output (MIMO) technology, which is enabled by geographical diversity and multiplexing techniques. As a result, the comprehension of structures of MIMO antennas operating at mmWave is imperative for the continued enhancement of performance. In comparing the efficacy of these designs, bandwidth, isolation, efficiency, gain, and radiation pattern are considered. In this paper, the most recent planar MIMO antenna designs, which are categorized as defected ground structures, Slot/Patch/Stub, MIMO Antenna Array, Dielectric Resonator Antenna, and Meta-Surface/Metamaterial Structures, are described. This paper also addresses the effects that slots, partial ground, and decoupling structures have on levels of isolation, bandwidth, and impedance matching. A comprehensive analysis of the design considerations and subsequent advancements is also provided in this paper. [ABSTRACT FROM AUTHOR]

Unlike the concentrated load in urban area base stations, the strong dispersion of loads in suburban or highway base stations poses significant challenges to traditional power supply methods in terms of efficiency and cost. High-voltage direct current (HVDC) remote supply have better application potential in this scenario due to their low transmission losses, attracting much attention. However, existing research has problems such as ambiguous optimal power supply distance under different voltage levels and a lack of behavioral models for converters. Therefore, this paper starts from the behavior of underlying converters, analyzes the loss composition of different converters in HVDC long-distance supply, and establishes a refined model for converters by determining the mathematical relationship between converter losses and operating power. Considering the economic feasibility of power supply solutions throughout the lifecycle, a modeling method is proposed that optimizes the voltage level of converters considering the behavior of converters for different supply distances. The optimal voltage level for different supply distances is discussed, and the effectiveness of the model is verified through examples, providing valuable guidance for optimizing the voltage level in HVDC long-distance supply for 5G base stations. [ABSTRACT FROM AUTHOR]

In order to implement the fifth generation (5G) communication system for a large number of users, the governments of many countries nominated the low 5G frequency band between 3.3 and 4.3 GHz. This paper proposes a wideband RFPA by designing the input matching network (MN) and output MN of the device using the simplified real frequency technique (SRFT) and the harmonic tuning network. The load-pull and source-pull is applied at multiple points for 100 MHz intervals over the bandwidth to obtain the optimum impedances at the output and input of the 10W Gallium Nitride (GaN) Cree CGH40010F device. To verify the design, the RFPA is simulated, and the performance is measured between 3.3 and 4.3 GHz. According to experimental findings, the measured drain efficiency (DE) throughout the whole bandwidth ranged from 57.5 to 67.5% at the output power of 40 dBm. Moreover, at the 1 dB compression point between 39.2 and 42.2 dBm output power, the drain efficiency (DE) achieves a high value of 81.2% with an output power of 42.2 dBm at a frequency of 3.3 GHz. The RFPA can obtain a maximum gain of 12.4 dB at 3.5 GHz. The linearity of the RFPA with a two-tone signal is measured and the value is less than -22 dBc all over the band. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of electromagnetic wave pollution as a new form of pollution in human society is attributed to the advancements in communication technology and the electronic information business. In addition to harming priceless electronic equipment, these electromagnetic radiation and interference issues brought on by electrical and electronic devices have a major negative influence on human productivity and wellbeing. The secret to getting rid of electromagnetic radiation interference (EMI) and improving performance is electromagnetic shielding technology. Metamaterial absorber is a type of metamaterial that absorb EMI radiation. The benefits of metamaterial absorbers include their lightweight, simple construction, and excellent absorptivity. Methods: This paper proposes a novel metamaterial absorber for EMI radiation absorption. It consists of dielectric layers, metamaterial shielding layer and transmission line. The reflection of radiation is reduced by miniaturization of metamaterials. Results and Discussion: Simulation results show that the proposed design has better performance as compared to existing methods. The operating frequency range is from 23.1 to 28.3 GHz. The values of S21 with and without shielding are -5 dB and -0.05 dB, and the shielding effectiveness is 10.10 dB and a maximum of 12.63 dB. [ABSTRACT FROM AUTHOR]

This paper proposes a broadband eight-antenna array design suitable for Fifth Generation New Radio (5G NR) smartphone applications. To cover the 5G NR bands n77/n78/n79 (3300–5000 MHz) and 5G NR-U n46 band (5150–5925 MHz), the single antenna array unit applied is a modified loop antenna element (MLAE) that can generate three different loop modes. To yield good multi-input multi-output (MIMO) performances, the designed MLAE is further arranged as an eight-antenna array, and the experimental results show that the overlapping 6 dB bandwidth can cover the bands-of-interest (3300–5925 MHz) with good isolation and total efficiency of >10 dB and 51–84%, respectively. Finally, good MIMO performances, such as an envelope correlation coefficient (ECC) of lower than 0.1 and desirable channel capacity (CC) of 37–40 bps/Hz, were calculated across the bands-of-interest. [ABSTRACT FROM AUTHOR]

This paper introduces a 12-element asymmetric mirror-coupled loop antenna for integration into 5G smartphones. The proposed antenna includes six identical asymmetrically mirrored (AM)-coupled building blocks, each consisting of two gap-coupled loop antennas, with each building block dimensioning a mere 12 × 7 mm2. The unique architecture of the proposed antenna yields an isolation performance exceeding 14 dB without the necessity for ancillary decoupling elements and effectively covers the dual-band 5G mobile frequency bands of 3.3-3.6 GHz and 4.8-5.0 GHz. The antenna was optimized using simulation software HFSS, and the results indicate an antenna's envelope correlation coefficient of less than 0.016 and an efficiency range of 72%-81%. Finally, the performance of single-hand and double-hand handset smartphone modes is discussed, which still exhibit good radiation and MIMO performance under both modes, demonstrating their stability in practical applications. Simulation and measurement results indicate that the proposed 12-element MIMO antenna holds great promise for 5G smartphone applications. [ABSTRACT FROM AUTHOR]

The rapid expansion of wireless communication systems has spurred a growing demand for adaptable multiple-input multipleoutput (MIMO) antennas capable of accommodating diverse frequency bands and operational environments. This paper presents a compact quad-port wide-band tuning-reconfigurable MIMO antenna tailored specifically for 5G applications operating within the sub-6 GHz spectrum. The proposed design enhances isolation levels (> 18 dB) and augments pattern diversity by utilizing four orthogonal radiating elements. Integrating a C-shaped monopole element with a matching stub facilitates frequency tuning via a varactor diode, ensuring a consistent radiation pattern. The lower and upper resonant bands could be fine-tuned by adjusting the varactor diode's reversebiased voltage within the allowed range of 0.5 to 10 V. These bands are 4 to 5.18 GHz and 5.45 to 6.65 GHz, respectively. The proposed antenna system's four C-shaped elements are placed on a 40 × 40 mm2 ground plane and mounted on a Rogers RT5880 substrate that is 0.8 mm thick with a relative permittivity of 2.2. This design is well suited for various wireless applications and cognitive radio networks due to its compatibility with sub-6 GHz frequency bands and wide-band tuning capabilities. [ABSTRACT FROM AUTHOR]

This paper presents the design and isolation enhancement of a filtering MIMO antenna with a radiation null for out-of-band suppressions suited for 5G sub-6 GHz communications. The MIMO antenna offers -10 dB impedance bandwidth functionality at the most prominent partial spectrum of the 5G NR n78 band for enabling wireless applications in base stations, ranging from 3.4 GHz to 3.61 GHz. To mitigate the redundancy of an RF filter and to achieve a strong filtering response, a radiation null is produced in the gain with four identical rectangular slots, which results in a significant gain drop of more than 8 dBi at the stopband. The geometrical design also allows 30 percent size reduction of single element. Subsequently, a closely spaced (0.11λ0) two-port MIMO antenna is implemented and with the utilization of the proposed rectangular shaped hollow stub parasitic element, the interelement isolation is significantly improved by more than 8 dB over the operational frequency range while retaining the filtering without any additional RF structure. The design simplification, peak gain of 5.4 dBi, near ideal response of diversity gain, ECC less than 0.03, congruency between simulated and measured results, and stable parameters make it a valuable choice for 3.5 GHz sub-6 GHz communications. [ABSTRACT FROM AUTHOR]

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most cellular systems, such as Bluetooth indoor positioning systems, due to multipath and non-line-of-sight (NLOS) propagation, indoor positioning accuracy is severely affected. In this paper, a comprehensive algorithm that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates is investigated, which is obtained using particle filtering. This algorithm allows us to explore new optimized methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by approximately 25.7% on average. [ABSTRACT FROM AUTHOR]

With the development of 5th-Generation Mobile Communication (5G) technology and the deployment of low-Earth orbit satellites, using satellites to locate 5G radiation sources is of great significance in commerce and the military as an important task of integrated sensing and communication. Recently, passive virtual aperture technology has been introduced into passive location to improve accuracy, but the existing method, using matched filters to search the Doppler information to realize the location, has the disadvantages of high complexity and poor range resolution. In this paper, an improved 5G radiation source location based on a virtual aperture is proposed, which uses the improved Golden Section search-fractional Fourier algorithm (GSS-FRFT) to improve the existing passive virtual aperture location methods. First, the received signals are coherently accumulated to convert the time gain into spatial gain, and the subcarrier phase information is extracted by Fast Fourier Transform based on the 5G signal characteristics to obtain the azimuth signal. Then, an improved high-order GSS-FRFT algorithm is proposed to analyze the Doppler information, and signal focusing and satellite ephemeris data are used to estimate the effective velocity and solve the radiation source location. The simulation results show that the proposed method can improve the location accuracy compared with other single-satellite location methods and has high resolution, high accuracy and low complexity compared with the existing passive virtual aperture location method. [ABSTRACT FROM AUTHOR]

Enhancing spectral efficiency in non-line-of-sight (NLoS) environments is essential as 5G networks evolve, surpassing 4G systems with high information rates and minimal interference. Instead of relying on traditional Orthogonal Multiple Access (OMA) systems to tackle issues caused by NLoS, advanced wireless networks adopt innovative models like Non-Orthogonal Multiple Access (NOMA), cooperative relaying, Multiple Input Multiple Output (MIMO), and intelligent reflective surfaces (IRSs). Therefore, this study comprehensively analyzes these techniques for their potential to improve communication reliability and spectral efficiency in NLoS scenarios. Specifically, it encompasses an analysis of cooperative relaying strategies for their potential to improve reliability and spectral efficiency in NLoS environments through user cooperation. It also examines various MIMO configurations to address NLoS challenges via spatial diversity. Additionally, it investigates IRS settings, which can alter signal paths to enhance coverage and reduce interference and analyze the role of Unmanned Aerial Vehicles (UAVs) in establishing flexible communication infrastructure in difficult environments. This paper also surveys effective energy harvesting (EH) strategies that can be integrated with NOMA for efficient and reliable energy-communication networks. Our findings show that incorporating these technologies with NOMA not only enhances connectivity and spectral efficiency but also promotes a stable and environmentally sustainable data communication system. [ABSTRACT FROM AUTHOR]

This paper studies the performance of hybrid digital-analog multi-user multipleinput multiple-output (MU-MIMO) downlink communication based on various antenna systems for 5G applications. The analysis is focused on comprehensive numerical simulations comparing hybrid beamforming schemes for collocated vs distributed phased array antennas (PAA) deployments in two indoor office environments. This study uses measured beamforming radiation patterns from two 28 GHz state-of-the-art PAAs. The channel models employed are the standardized statistical 3GPP 38.901 indoor channel models implemented in the QuaDRiGa software. A beam selection algorithm is implemented to maximize the achievable sum rate, assuming either matched-filtering or zero-forcing precoding. The evaluated figures of merit are the gain of the RF power amplifier, the per-user signal-to-interference-plus-noise ratio (SINR), and the resulting achievable sum-rate capacity. Based on the results, the distributed deployment scenario always shows a higher SINR and achievable sum-rate capacity at the user locations while requiring a lesser amplification of the conducted power. Specifically, the largest PAA with slant-polarized 16 x 4 elements producing 16 horizontal analog beams in combination with zeroforcing digital precoding proved to be the best solution in both open and mixed indoor office environments in absolute values. On the other hand, the array based on the same type of elements but in a more compact realization with 4 x 4 elements, but with beams arranged as 8 horizontal times 2 vertical, offered the most significant relative gains. [ABSTRACT FROM AUTHOR]

In this paper, different concepts of reconfigurable RF-MEMS attenuators for beamforming applications are proposed and critically assessed. Capitalizing on the previous part of this work, the 1-bit attenuation modules featuring series and shunt resistors and low-voltage membranes (7–9 V) are employed to develop a 3-bit attenuator for fine-tuning attenuations (<−10 dB) in the 24.25–27.5 GHz range. More substantial attenuation levels are investigated using fabricated samples of coplanar waveguide (CPW) sections equipped with Pi-shaped resistors aiming at attenuations of −15, −30, and −45 dB. The remarkable electrical features of such configurations, showing flat attenuation curves and limited return losses, and the investigation of a switched-line attenuator design based on them led to the final proposed concept of a low-voltage 24-state attenuator. Such a simulated device combines the Pi-shaped resistors for substantial attenuations with the 3-bit design for fine-tuning operations, showing a maximum attenuation level of nearly −50 dB while maintaining steadily flat attenuation levels and limited return losses (<−11 dB) along the frequency band of interest. [ABSTRACT FROM AUTHOR]

A miniaturized and wideband four-port multiple-input multiple-output (MIMO) antenna pair for Wi-Fi mobile terminals application is proposed. The proposed antenna pair consists of four multi-branch antenna elements arranged orthogonally, with an overall size of 40 × 40 × 3.5 mm3 and each antenna element size of 15.2 × 3.5 mm × 0.8 mm3. The performance of the proposed antenna shows the advantages of a wide frequency band, low mutual coupling, high efficiency, and a compact structure. The wideband characteristics of the antenna elements are achieved through multi-mode resonance. The suppression of coupling is accomplished by strategically positioning the four compact antenna elements to ensure their maximum radiation directions are orthogonal, thus eliminating the need for an additional decoupling structure. In this paper, the proposed antenna is optimized in terms of the parameters then simulated and measured. The simulated results illustrate that an impedance bandwidth of the antenna is about 15% (5.06~5.88 GHz) with S11 < −10 dB, excellent port isolation exceeds 20 dB between all ports, a high radiation efficiency ranges from 51.2% to 89.9%, the maximum gain is 4.5 dBi, and the ECCs are less than 0.04. The measured results show that the −10 dB impedance bandwidth of the antenna is about 13% (5.13~5.80 GHz), the isolation between the antenna elements is better than 21 dB, the radiation efficiency ranges from 51.8% to 92.3%, the maximum gain is 5.3 dBi, and the ECCs are less than 0.05. The proposed four-port MIMO antenna works on the 5G LTE band 46 and Wi-Fi 6E operating bands. As a mobile terminal antenna, the proposed design scheme demonstrates excellent performance and applicability, fulfilling the requirements for 5G mobile terminal applications. [ABSTRACT FROM AUTHOR]

Polar codes have garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provable capacity achieving capability. They have been standardized to be used for encoding information on the control channels in 5G wireless networks due to their robustness for short codeword lengths. The conventional approach to generate polar codes is to recursively use 2 × 2 kernels and polarize channel capacities. This approach however, has a limitation of only having the ability to generate codewords of length N o r i g = 2 n form. In order to mitigate this limitation, multiple techniques have been developed, e.g., polarization kernels of larger sizes, multi-kernel polar codes, and downsizing techniques like puncturing or shortening. However, the availability of so many design options and parameters, in turn makes the choice of design parameters quite challenging. In this paper, the authors propose a novel polar code construction technique called Adaptive Segmented Aggregation which generates polar codewords of any arbitrary codeword length. This approach involves dividing the entire codeword into smaller segments that can be independently encoded and decoded, thereby aggregated for channel processing. Additionally a rate assignment methodology has been derived for the proposed technique, that is tuned to the design requirement. [ABSTRACT FROM AUTHOR]