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The deployment of fifth-generation mobile network (5G), beyond 5G and sixth-generation mobile network platforms encounters challenges of blockage, interference, and path loss in radio mobile environments. Metasurfaces provide a promising solution to address these limitations. In this paper, we present a methodology for developing ultrathin flexible metasurface-based frequency selective surfaces (FSSs). Our approach combines thermal evaporation for metallic thin films with a macroscopic metasurface mask (something analogous to screen-printing but using thermal evaporation instead of inks). As a proof of concept, we fabricate a sub-6 GHz metasurface-based FSS using gold deposition on a flexible polyethylene terephthalate substrate. Experimental results are validated through numerical full-wave simulations using COMSOL Multiphysics and equivalent-circuit model simulations. The metasurface operates within the primary frequency band utilized in 5G networks (3–5 GHz), indicating its potential applicability across a wide range of flexible, conformal, and wearable devices. The fabricated FSS can be installed on surfaces of any shape, such as flat or curved windows, as well as on walls or other external surfaces. This methodology offers practical solutions for wireless communications and enhancing signal transmission in diverse environments. [ABSTRACT FROM AUTHOR]

An experimental demonstration of directivities exceeding the fundamental Kildal limit, a phenomenon called superdirectivity, is provided for spherical high-index dielectric antennas with an electric dipole excitation. A directivity factor of about 10 with a total efficiency of more than 80% for an antenna having a size of a third of the wavelength was measured. High directivities are shown to be associated with constructive interference of particular electric and magnetic modes of an open spherical resonator. Both analytic solutions for a point dipole and a full-wave rigorous simulation for a realistic dipole antenna were employed for optimization and analysis, yielding an excellent agreement between experimentally measured and numerically predicted directivities. The use of high-index low-loss ceramics can significantly reduce the physical size of such antennas while maintaining their overall high radiation efficiency. Such antennas can be attractive for various high-frequency applications, such as antennas for the Internet of Things, smart city systems, 5G network systems, and others. The demonstrated concept can be scaled in frequency. [ABSTRACT FROM AUTHOR]

Summary: A novel antenna system that utilizes multiple‐input and multiple‐output (MIMO) technology to suit the requirements of 5G applications is proposed in this article. The antenna has a wide operating bandwidth and high isolation in n257/n258/n261 5G bands. The suggested arc‐shaped MIMO antenna is composed of four similar patch units with modified ground planes arranged in a four‐port configuration and is made on a Rogers RT/duroid 5880 substrate, which measures 31.891 × 37.5885 × 0.508 mm3. The prototype of the suggested MIMO antenna is realized to confirm the obtained simulated results and validate the proposed design. The four‐port MIMO antenna features a broad frequency range of 7.3 GHz from 21.8 to 29.1 GHz, a peak gain of 5.76 dBi at 29 GHz, and a good isolation less than −18 dB. The proposed antenna's MIMO performance is evaluated by analyzing several diversity parameters. The findings of the evaluation demonstrate an envelope correlation coefficient (ECC) value of less than 0.001, a diversity gain (DG) value exceeding 9.995 dB, and an average mean effective gain (MEG) of −3 dB within the operational frequency band. The suggested MIMO antenna's compact size and impressive performance make it a suitable choice for intended n257/n258/n261 5G NR networks. [ABSTRACT FROM AUTHOR]

Summary: The millimeter‐wave (mmW) band has been chosen to obtain multi‐gigabit per second in the fifth generation (5G) communication and beyond. The knowledge of this frequency band is still the focus of research today. After UTI announced its choice of mmW for 5G communication, massive studies were carried out on this band. Among these studies, many optimization methods were proposed to reduce the impact of degradation sources. In this paper, we propose a new method to optimize the system error vector magnitude (EVM) of complex systems with many different calibration sources. A difference of 0.1% is observed between our optimization method and old methods. This small improvement of the EVM system can push the 3GPP system EVM (EVM at the receiver) limits by a few centimeters, which is not negligible in a high‐frequency transmission. Moreover, we have also proposed a new method to compute the throughput that takes into account the TX and RX directional antenna heights. The measurement campaigns and simulation results have shown an improvement from 0% to 6% of throughput. The results depend on indoor environment study and different obstacles in NLOS (non‐line of sight) conditions. [ABSTRACT FROM AUTHOR]

Continuous deployment has been practiced for many years by companies developing web‐ and cloud‐based applications. To succeed with continuous deployment, these companies have a strong collaboration culture between the operations and development teams. In addition, these companies use AI, analytics, and big data to assist with time‐consuming postdeployment activities such as continuous monitoring and fault identification. Thus, the term AIOps has evolved to highlight the importance and difficulty of maintaining highly available applications in a complex and dynamic environment. In contrast, software‐intensive embedded systems often provide customer product‐related services, such as maintenance, optimization, and support. These services are critical for these companies as they provide significant revenue and increase customer satisfaction. Therefore, the objective of our study is to gain an in‐depth understanding of the impact of continuous deployment on product‐related services provided by software‐intensive embedded systems companies. In addition, we aim to understand how AIOps can support continuous deployment in the context of software‐intensive embedded systems. To address this objective, we conducted a case study at a large and multinational telecommunications systems provider focusing on the radio access network (RAN) systems for 4G and 5G networks. The company provides RAN products and three complementing services: rollout, optimization, and customer support. The results from the case study show that the boundaries between product‐related services become blurry with continuous deployment. In addition, product‐related services, which were conducted in sequence by independent projects, converge with continuous deployment and become part of the same project. Further, AIOps platforms play an important role in reducing costs and increasing postdeployment activities' efficiency and speed. These results show that continuous deployment has a profound impact on the software‐intensive system's provider service organization. The service organization becomes the connection between the R&D organization and the customer. In order to cope with the increased speed of releases, deployment and postdeployment activities need to be largely automated. AIOps platforms are seen as a critical enabler in managing the increasing complexity without increasing human involvement. [ABSTRACT FROM AUTHOR]

A four-port low-profile broadband patch antenna is designed for fifth-generation (5G) multi-input multi-output (MIMO) mobile applications. The designed antenna loads shorting pins S1 and S2 on a square patch with etched fan-leaf slits, making the parasitic patch work more visible. In addition, loading shorting pin S3 excites a low-frequency resonant mode, which enables the antenna to completely cover frequency ranges of 3.3–5 GHz (5G N77 and N79 bands). The effective height of the designed antenna is only 3.7 mm (0.05λ at 4.15 GHz). The antenna achieves a good balance between impedance bandwidth and profile, realizing wide bandwidth coverage. To confirm the precision of the results, the designed antenna is fabricated and measured. The measured results show that the −6 dB impedance bandwidth covers 3.3–5 GHz. All the isolation between ports are superior to 12 dB. The envelope correlation coefficients (ECCs) is below 0.15 and the overall efficiency is between 50% and 90% in the 3.3–5 GHz. [ABSTRACT FROM AUTHOR]

This paper presents a four-port multiple-input multiple-output (MIMO) magneto-electric dipole antenna array with high gain and high isolation for 5G millimeter-wave communications. Each antenna contains an eight-way power divider, an eight-element magneto-electric dipole antenna array, a metal rectangular ring, and a dielectric slab. The proposed magneto-electric dipole antenna array has high radiation gain. The metal rectangular ring is applied to not only support the dielectric slab but suppress the surface wave propagation and thus the mutual coupling can be reduced. A further increase in the isolation performance can be realized based on the polarization diversity. The simulated and measured impedance bandwidths at 10 dB return losses are 24–31.86 GHz (28.1%) and 24.12–32 GHz (28.1%), respectively. The simulated and measured isolation levels are larger than 25 and 20 dB, respectively. The simulated and measured realized peak gains at 30 GHz are 20.5 and 19.2 dBi, respectively. [ABSTRACT FROM AUTHOR]

In the article, the extreme problem of finding the optimal placement plan of 5G base stations at certain points within a linear area of finite length is set. A fundamental feature of the author's formulation of the extreme problem is that it takes into account not only the points of potential placement of base stations but also the possibility of selecting instances of stations to be placed at a specific point from a defined excess set, as well as the aspect of inseparable interaction of placed 5G base stations within the framework of SON. The formulation of this extreme problem is brought to the form of a specific combinatorial model. The article proposes an adapted branch-and-bounds method, which allows the process of synthesis of the architecture of a linearly oriented segment of a 5G network to select the best options for the placement of base stations for further evaluation of the received placement plans in the metric of defined performance indicators. As the final stage of the synthesis of the optimal plan of a linearly oriented wireless network segment based on the sequence of the best placements, it is proposed to expand the parametric space of the design task due to the specific technical parameters characteristic of the 5G platform. The article presents a numerical example of solving an instance of the corresponding extremal problem. It is shown that the presented mathematical apparatus allows for the formation of a set of optimal placements taking into account the size of the non-coverage of the target area. To calculate this characteristic parameter, both exact and two approximate approaches are formalized. The results of the experiment showed that for high-dimensional problems, the approximate approach allows for reducing the computational complexity of implementing the adapted branch-and-bounds method by more than six times, with a slight loss of accuracy of the optimal solution. The structure of the article includes Section 1 (introduction and state-of-the-art), Section 2 (statement of the research, proposed models and methods devoted to the research topic), Section 3 (numerical experiment and analysis of results), and Section 4 (conclusions and further research). [ABSTRACT FROM AUTHOR]

In the evolving landscape of Industry 4.0, the integration of advanced wireless technologies into manufacturing processes holds the promise of unprecedented connectivity and efficiency. In particular, the data transmission in a heavy industry environment needs stable connectivity with mobile operators. This paper deals with the performance study of 4G and 5G mobile signal coverage within a complex factory environment. For this purpose, a cost-effective and portable measurement setup was realized and used to provide long-term measurement campaigns monitoring and recording several key parameter indicators (KPIs) in 4G/5G downlink and upload. To support the reproducibility of the provided study and other research activities, the measured dataset is publicly available for download. Among others findings, the obtained results show how the performance of 4G/5G is influenced by a heavy industry environment and of the time of day on the network load. [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]

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]

To ensure the safe and stable operation of 5G base stations, it is essential to accurately predict their power load. However, current short‐term prediction methods are rarely applied rationally in pertinent circumstances to the features of base station power load over time. For high accuracy and generalization capabilities, this work proposes a hybrid approach that combines gated recurrent unit (GRU) with particle swarm optimization (PSO) and completes ensemble empirical mode decomposition with adaptive noise (CEEMDAN). The complex load is decomposed into multiple components to improve the fit of the neural network. To deal with the nonlinearity that constrains the modal aliasing and data noise, CEEMDAN is used to reconstruct the trend and noise sequences. The GRU network is utilized to improve the neural network fitness and obtain long‐term features. In addition, PSO is used to optimize the number of neurons and the learning rate of the GRU. Compared with existing neural network GRUs, the RMSE is reduced by 16.6, the mean absolute error is reduced by 11.97, and the coefficient of R2 is improved by 0.13, indicating that the model has a better fitting effect. The comparisons prove that the proposed model has better accuracy than the existing methods. [ABSTRACT FROM AUTHOR]

The rapid deployment of 5G networks necessitates innovative solutions for efficient and dynamic resource allocation. Current strategies, although effective to some extent, lack real-time adaptability and scalability in complex, dynamically-changing environments. This paper introduces the Dynamic Resource Allocator using RL-CNN (DRARLCNN), a novel machine learning model addressing these shortcomings. By merging Convolutional Neural Networks (CNN) for feature extraction and Reinforcement Learning (RL) for decision-making, DRARLCNN optimizes resource allocation, minimizing latency and maximizing Quality of Service (QoS). Utilizing a state-of-the-art “5G Resource Allocation Dataset”, the research employs Python, TensorFlow, and OpenAI Gym to implement and test the model in a simulated 5 G environment. Results demonstrate the effectiveness of DRARLCNN, showcasing an impressive R2 score of 0.517, MSE of 0.035, and RMSE of 0.188, surpassing existing methods in allocation efficiency and latency. The DRARLCNN model not only outperforms existing methods in allocation efficiency and latency but also sets a new benchmark for future research in dynamic 5G resource allocation. Through its innovative approach and promising results, DRARLCNN opens avenues for further advancements in optimizing resource allocation within dynamic 5G networks. [ABSTRACT FROM AUTHOR]

Our society is being transformed by the technology emergence and the industrial revolution. The advances in the internet and artificial intelligence are reshaping the means of education, profoundly changing the ways of teaching and learning. This paper studies the pattern of how the new 5th generation blended campus network is applied to aid the new generation of intelligence teaching. This pattern is the implementation of national major policies and the measure of cultivating people. This paper introduces a new model for the intelligence teaching system. Based on the new model, distance interaction teaching system, VR practicing teaching system, intelligence testing system, and higher education intelligence decision system are developed. This model can be the basis of the informatization of future education. [ABSTRACT FROM AUTHOR]

Smart farming is revolutionizing agriculture by integrating advanced technologies to enhance productivity, efficiency, and sustainability. This paper proposes a novel, 5G-enabled Pest and Disease Detection and Response System (PDDRS) that synergizes environmental sensor data with image analytics for comprehensive Plant Disease Detection (PDD). By leveraging the high bandwidth and ultra-low latency capabilities of 5G, our integrated system surpasses traditional communication technologies, facilitating real-time data analytics and immediate intervention strategies. We introduce two Machine Learning (ML) models: an image-based Mask R-CNN with FPN, which achieves a precision of 91.1% and an accuracy of 95.1%, and an environmental-based FFNN + LSTM model, evaluated for ACC, AUC, and F1-Score, showing promising results in disease forecasting. Our experiments demonstrate that the PDDRS significantly enhances throughput and latency performance under various connected devices, showcasing a scalable, cost-effective solution suitable for next-generation smart farming. These advancements collectively empower the PDDRS to deliver actionable insights, enabling targeted applications such as precise pesticide deployment, and stand as a testament to the potential of 5G in agricultural innovation. [ABSTRACT FROM AUTHOR]

Railway communication is undergoing a transitional period worldwide, and 5G for railway (5G-R), which has been adopted by the Railway International Union (UIC) in China and in many other countries, which is a common concern all over the world. The 2100 MHz frequency band, which ranks among the top three mainstream frequency bands for public 5G network deployment globally, has recently been issued by MIIT for a 5G-R trial in China, and the frequency is fairly close to 5G-R frequency band of 1900 MHz in Europe. Propagation study for railway communication, especially for mainline, which is the most common and widely used scenario, is of great importance, because it is closely related to passengers' lives and properties. In this article, based on the 5G-R dedicated network testing environment constructed along the test line of loop railway of National Railway Track Test Center of China, the 2100 MHz 5G-R propagation measurement campaign is conducted, with an in-service SS-RSRP signal-based passive 2100 MHz large-scale channel testing system, as well as a SDR-based 2100 MHz 5G-R channel sounding system, based on which the large-scale as well as small-scale channel characteristics are derived and extensively analyzed. With data derived from the passive testing system, the classical FI, CI as well as TR 38.901 large-scale channel models are properly fitted and compared by calculating RMSE as well as MAE values. Moreover, based on the SDR-based channel sounding system, conclusions on the relationship between the parameters of multi-path component numbers, RMS time spread, received power and distance between the transmitter and the receiver are drawn. The 5G-R system studied in this letter is symmetric FDD communication system, apart from the 2 aspects of channel modeling characteristics, which are large-scale and small-scale complementing each other, the research methodology adopted of the letter also has two aspects, passive measurement, as well as active measurement, and both methods have their own advantages and different focuses, which can also complements each other. Relevant research results of this letter will be helpful for facilitating the R&D, deployment, as well as network optimization of a future mobile communication system under railway mainline scenario. [ABSTRACT FROM AUTHOR]

The internet of medical things (IoMT) has transformed the healthcare sector by facilitating real-time monitoring, remote patient care, and tailored healthcare solutions. However, the challenge of upholding a high standard quality of service (QoS) in IoMT implementations remains a pressing issue. This article delves into the possibilities of utilizing 5G networks and smart techniques to optimize QoS within IoMT systems. By capitalizing on the capabilities of 5G networks, including substantial bandwidth, minimal latency, and extensive connectivity, in conjunction with intelligent methods such as machine learning and predictive analytics, this paper introduces novel strategies to enhance QoS in IoMT environments. The summary underscores the advantages of these methods in elevating network dependability, diminishing latency, enhancing data transmission efficiency, and enabling resource allocation efficiency in IoMT deployments. Additionally, it explores the potential ramifications of these developments on healthcare outcomes, patient contentment, and the overall effectiveness of the healthcare system. The conclusions propose that by maximizing QoS through 5G networks and intelligent techniques, IoMT holds the potential to significantly enhance the delivery of healthcare services, fostering a more interconnected and efficient healthcare ecosystem in the process innovation. [ABSTRACT FROM AUTHOR]

In this paper, we design and simulate a 28/38 GHz dual-band multiple-input multiple-output (MIMO) patch antenna array that operates in the FR2 frequency band (28 GHz and 38 GHz). This antenna array comprises four similar patch antennas with a rectangular "L minus two slots" shape. In addition, it applies to 5G electronic components such as a smartphone. We used high-frequency structure simulator (HFSS) software to perform the design and simulation for this antenna. In addition, this proposed antenna array provides better performance, such as; bandwidth around 28 GHz is equal to 0.69 GHz and 38 GHz is equal to 0.86 GHz, equal gains 5. 9 dB at 28 GHz and 9 dB at 38 GHz, directivities are 6.3 dB at 28 GHz and 9.4 dB at 38 GHz, the efficiency of 95.38% at 28 GHz, and efficiency of 96.53% at 38 GHz. [ABSTRACT FROM AUTHOR]

This study proposes a deep learning method for pavement defect detection, focusing on identifying potholes and cracks. A dataset comprising 10,828 images is collected, with 8662 allocated for training, 1083 for validation, and 1083 for testing. Vehicle attitude data are categorized based on three-axis acceleration and attitude change, with 6656 (64%) for training, 1664 (16%) for validation, and 2080 (20%) for testing. The Nvidia Jetson Nano serves as the vehicle-embedded system, transmitting IMU-acquired vehicle data and GoPro-captured images over a 5G network to the server. The server recognizes two damage categories, low-risk and high-risk, storing results in MongoDB. Severe damage triggers immediate alerts to maintenance personnel, while less severe issues are recorded for scheduled maintenance. The method selects YOLOv7 among various object detection models for pavement defect detection, achieving a mAP of 93.3%, a recall rate of 87.8%, a precision of 93.2%, and a processing speed of 30–40 FPS. Bi-LSTM is then chosen for vehicle vibration data processing, yielding 77% mAP, 94.9% recall rate, and 89.8% precision. Integration of the visual and vibration results, along with vehicle speed and travel distance, results in a final recall rate of 90.2% and precision of 83.7% after field testing. [ABSTRACT FROM AUTHOR]

The sharing of mobile network infrastructure has become a key topic with the introduction of 5G due to the high costs of deploying such infrastructures, with neutral host models coupled with features such as network function virtualization (NFV) and network slicing emerging as viable solutions for the challenges in this area. With this in mind, this work presents the design, implementation, and test of a flexible infrastructure-sharing 5G network architecture capable of providing services to any type of client, whether an operator or not. The proposed architecture leverages 5G's network slicing for traffic isolation and compliance with the policies of different clients, with roaming employed for the authentication of users of operator clients. The proposed architecture was implemented and tested in a simulation environment using the UERANSIM and Open5GS open-source tools. Qualitative tests successfully validated the authentication and the traffic isolation features provided by the slices for the two types of clients. Results also demonstrate that the proposed architecture has a positive impact on the performance of the neutral host network infrastructure, achieving 61.8%-higher throughput and 96.8%-lower packet loss ratio (PLR) in a scenario sharing the infrastructure among four clients and eight users when compared to a single client with all the network resources. [ABSTRACT FROM AUTHOR]

A novel aperture‐shared dual‐wideband 5G antenna with dual polarization in the sub‐6 GHz band and multi‐input multi‐output (MIMO) function in the 28‐GHz band is presented in this work. A dual‐polarized megnetoelectric dipole (ME‐dipole) with wide bandwidth is introduced in the sub‐6 GHz band. Based on the partial structure reuse method, four 2 × 2 substrate integrated waveguide (SIW) cavity‐backed patch arrays are integrated into the electric dipole structure of the ME‐dipole to construct a 28‐GHz 2 × 2 MIMO system. Two high‐order SIW cavity modes that cooperate with patch modes are used to enhance bandwidth in the 28‐GHz band. For demonstration, a prototype of the proposed antenna was fabricated and measured. The simulated results are in good agreement with the measured results, showing wide bandwidths of 39.6% and 10.85% in the sub‐6 GHz and the 28‐GHz bands, respectively. In addition, excellent measured in‐band and cross‐band isolations of over 44.4 dB and 45.2 dB are obtained, respectively. [ABSTRACT FROM AUTHOR]

In the realm of the fifth-generation (5G) wireless cellular networks, renowned for their dense connectivity, there lies a substantial facilitation of a myriad of Internet of Things (IoT) applications, which can be supported by the massive machine-type communication (MTC) technique, a fundamental communication framework. In some scenarios, a large number of machine-type communication devices (MTCD) may simultaneously enter the communication coverage of a target base station. However, the current handover mechanism specified by the 3rd Generation Partnership Project (3GPP) Release 16 incurs high signaling overhead within the access and core networks, which may have negative impacts on network efficiency. Additionally, other existing solutions are vulnerable to malicious attacks such as Denial of Service (DoS), Distributed Denial of Service (DDoS) attacks, and the failure of Key Forward Secrecy (KFS). To address this challenge, this paper proposes an efficient and secure handover authentication protocol for a group of MTCDs supported by blockchain technology. This protocol leverages the decentralized nature of blockchain technology and combines it with certificateless aggregate signatures to mutually authenticate the identity of a base station and a group of MTCDs. This approach can reduce signaling overhead and avoid key escrow while significantly lowering the risk associated with single points of failure. Additionally, the protocol protects device anonymity by encrypting device identities with temporary anonymous identity markers with the Elliptic Curve Diffie–Hellman (ECDH) to abandon serial numbers to prevent linkage attacks. The resilience of the proposed protocol against predominant malicious attacks has been rigorously validated through the application of the BAN logic and Scyther tool, underscoring its robust security attributes. Furthermore, compared to the existing solutions, the proposed protocol significantly reduces the authentication cost for a group of MTCDs during handover, while ensuring security, demonstrating commendable efficiency. [ABSTRACT FROM AUTHOR]

In this manuscript, we present a novel deployment protection method aimed at safeguarding aeronautical radio altimeters (RAs) from interference caused by fifth-generation (5G) telecommunication base stations (BSs). Our methodology involves an integrated interference model for defining prohibited zones and utilizes power control and angle shutoff methods to mitigate interference. First, to ensure reliable protection, we define both horizontal and vertical prohibited zones and investigate their variations to immunize RA against 5G interference. Second, we validate the effectiveness of the model in various operational scenarios, analyzing the influence of factors such as base station types, antenna parameters, flight altitude, and aircraft attitudes to cover a wide range of real-world scenarios. Third, to mitigate interference, we propose and analyze the power control and angle shutoff methods through simulation for the RMa prohibited zone. Our results demonstrate the efficacy of the deployment protection method in safeguarding RAs from 5G interference, providing guidance for interference protection during civil aviation operations and base station deployment near airports. [ABSTRACT FROM AUTHOR]

The error performance of the 5G low‐density parity‐check codes is significantly impacted by the update order of layers. At present, the row degree (RD) and the number of punctured bits (PBs) are widely used to decide the update order of layers. Here, the authors propose a metric to assess the soft message recovery speed of coded bits and then suggest updating layers with the lowest RD first rather than those with the least PBs first. Besides, a new criterion is introduced to further determine the update order of layers with the same number of PBs and the same RD. The resulting reordered layered schedule yields better error performance and faster convergence speed than the prior arts. [ABSTRACT FROM AUTHOR]

In this letter, an optimal calibration factor for mutual information effective signal‐to‐interference‐plus‐noise ratio (SINR) mapping (MIESM) scheme in fifth‐generation new radio (5G NR) is provided. By applying the optimal calibration factor to the MIESM scheme, the estimation accuracy of the effective SINR can be improved. The optimal calibration factor minimizes the mean squared error (MSE) of the difference between the estimated effective SINR and the required SNR under additive white Gaussian noise (AWGN) at a block error rate (BLER) of 10%. Simulation results show that the optimized MIESM scheme outperforms the non‐optimized MIESM scheme. [ABSTRACT FROM AUTHOR]

A 90° hybrid coupler operating at a central frequency of 5.40 GHz is introduced, offering high-performance characteristics with compact dimensions of 616.65 mm² (33.3 mm × 18.5 mm). These features are achieved while maintaining a design that makes it easy to produce. The unique aspect of this microstrip FR4 substrate-based design is the consistent S-parameters, which remain steady despite changes in structural dimensions, thereby making it adaptable to fabrication variations. The reported S-parameters measured in 5.4 GHz are as follows:|S11|= –29.46 dB,|S21|= –4.11 dB,|S31|= –3.96 dB, and|S41|= –21.23 dB. This hybrid coupler operates over a bandwidth of 0.8 GHz (16%), demonstrating remarkable performance within this spectrum. In addition to its design, the coupler exhibits robust resilience against changes in substrate parameters and structural dimensions, ensuring reliability during the fabrication process. Following thorough simulation studies, a physical prototype of the coupler was constructed and subjected to laboratory measurements. The experimental results align closely with the simulation data, validating the accuracy and predictability of the design. In comparison with other studies and designs documented in the literature, this compact, high-performance 90° hybrid coupler exhibits clear advantages in terms of size, isolation, phase deviation, and structural complexity. Therefore, the benefits and applicability of this presented structure in the context of microwave circuits and systems are underscored. It's noteworthy to mention that the central frequency of 5.4 GHz falls within the sub-6 GHz 5G band range. [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]

In this paper we describe a class of printed patch antennas that involve 3 metal layers completely integrated within a single dielectric, which are of very high efficiency and significant gain. The antennas presented have dual linear polarization and sufficient impedance matching bandwidth to be suited for sub-6 5G applications, producing advantageous antenna arrays monolithically integrated into a single planar PCB that are thin and lightweight. The feeding mechanism of the antennas is through an intermediate dedicated metal layer designed appropriately as a coupler, coupling the input power at the feeding ports of the structure to the antenna without a direct metal contact to the radiating patch. The multilayer design allows monolithic integration of multi-element combiners and phase shifters within the PCB of antenna arrays and results in compact monolithic scanning arrays. Theoretical full-wave simulations and measurements of fabricated prototypes are in very good agreement and validate the proposed designs. [ABSTRACT FROM AUTHOR]

This research presents the design and analysis of a compact MIMO antenna tailored for 5G millimeter-wave applications, specifically targeting bands N257, N260, and N262. The antenna, characterized by its straightforward design, maintains compact dimensions of 10 mm × 16 mm while delivering exceptional performance with high gain. Employing Rogers RT/Duroid 5880 substrate material with a thickness of 0.508 mm, the antenna consists of two crescent-shaped radiating elements (patches) situated on the top surface of the dielectric material, complemented by a slotted ground on the bottom. The radiating elements are fed through a 50-Ω microstrip line. Operating across three distinct bands, the antenna's capabilities are outlined as follows: the first band spans from 27.2 to 29 GHz, centering around 28 GHz; the second band encompasses the frequency range from 34 to 40.2 GHz, with a center frequency of 39 GHz achieved through slotting crescent-shaped radiating elements; the third band, ranging from 47.5 to 51.3 GHz with a center frequency of 48.7 GHz, is attained by engraving circular slots on the ground. To validate simulation outcomes, a hardware prototype of the antenna is manufactured, showcasing excellent agreement between simulations and measurements. The antenna design is implemented using the CST Microwave Studio software tool and is benchmarked against existing literature. Key attributes of the proposed antenna include its compact size, simple geometry, wide bandwidth, and high gain. The antenna's favorable MIMO parameters (ECC, TARC, DG, and CCL), coupled with minimal spacing between elements, position it as a promising candidate for forthcoming 5G millimeter-wave communication applications. [ABSTRACT FROM AUTHOR]

A novel design for Vivaldi antenna is introduced to operate in more than one frequency band in the millimeter-wave spectrum range with high gain. The proposed Vivaldi antenna is planar and printed on both sides of Rogers 3003C flexible substrate. A parasitic annular ring is added to each arm of the Vivaldi antenna to adjust the impedance matching and maximize the gain. The dimensions of the antenna are optimized using the CST microwave simulator to obtain the best impedance matching bandwidths and highest gain in a compact-size antenna. The 28-GHz band is then selected due to its importance to enhance the gain and improve the operating bandwidth for the 5G applications. A gain of 10 dBi and bandwidth of 6.1 GHz are obtained at 28 GHz. A multiple-input multiple-output (MIMO) antenna system is then designed for pattern diversity for the fifth-generation mobile applications. The performance of the MIMO system is evaluated regarding the envelope correlation coefficient and the diversity gain showing good results. The optimized antenna is fabricated and its return loss and radiation patterns are measured showing good consent between the simulations and the practical work. The MIMO antenna system is also fabricated, and its performance is measured regarding the reflection and coupling coefficients showing good agreement between the measurements and simulations. [ABSTRACT FROM AUTHOR]

Summary: Ultra‐accurate indoor localization/positioning technology is rapidly gaining interest in 5G and beyond (B5G) communications. Achieving 0.1 m level of precise indoor localization is a significant challenge that can be resolved using channel state information (CSI) of wireless signals from nearby access points. The complex indoor propagation issues like shadowing, blockage effects, and multi‐path fading diminish CSI, affecting precise position/location accuracy. Thus, to achieve ultra‐accurate localization, a novel MOIL framework is proposed using a deep learning BiLSTM model and CSI features in an efficient and optimized manner. The proposed MOIL integrates two functional blocks, SecLOP and CordNet. SecLOP conceals multi‐path effects and noise to optimize the input information using sequential responses of signals. CordNet minimizes precise position/location errors by taking all combinations of optimized signal features from the SecLOP block. Extensive simulation experiments were conducted to validate MOIL in different indoor scenarios, such as line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS). Moreover, through a substantial ablation study, the efficiency of the proposed framework is validated/verified. The results outperformed existing works by providing cm‐level accuracy of 1 cm in LOS and 1.5 cm in NLOS scenarios. The proposed work outperformed the literature by 31.3% in LOS and 25.30% in NLOS scenarios. [ABSTRACT FROM AUTHOR]

Edge computing (EC) aided Internet of Things (IoT) based applications require real-time processing as well as high-volume data-intensive services as 5G networks evolve. It is difficult to fit IoT services into available edge nodes (ENs) while maintaining performance measures on quality of service (QoS) because of the heterogeneity, restricted resources, and changing resource demand of IoT applications. This study aims to examine a quantum healthcare model that is built on mobile edge computing networks linked with smart IoT. Serverless computing with edge computing may handle quick or small-scale tasks effectively at edge devices, lowering latency. Moreover, serverless edge computing now faces significant hurdles from security and processing performance. In order to provide trustworthy and secure edge serverless services, it is possible to use blockchain technology to boost processing speed and quantum computing to enhance security. In terms of decreasing dependency on IoT cloud analytics or storage facilities, the test results were promising. Lastly, we cover the many aspects that impact the viability of integrating an edge-IoT ecosystem, such as design, capability requirements, functional challenges, and selection criteria. [ABSTRACT FROM AUTHOR]

Communication services that are dependable are crucial, particularly during emergencies when the regular infrastructure for communication may be disrupted or nonexistent. In such situations, device-to-device (D2D) communication can be a helpful choice since it allows user equipment (UE) that is close to one another to connect directly, bypassing the cellular network infrastructure. The primary focus of this thesis is the application of D2D communication in a decentralized emergency scenario with a damaged eNodeB. The main objective is to find an appropriate strategy for finding and selecting D2D couples by simulating several methods in MATLAB. This study compares three D2D pair selection algorithms: distance-based, Signal-to-Interference and Noise Ratio (SINR)-based, and data rate-based distance-based. The simulation results show that the data rate-based strategy is the most effective method for selecting D2D couples in emergency scenarios. In contrast to algorithms that rely on distance and SINR, this one reduces the chance of an outage by 20%. Bit error rate (BER), capacity, spectral efficiency, and energy efficiency are the three types of links that are assessed: direct links, relay links, and UE relay links. The results show that, with the lowest BER and maximum data throughput, the direct link is the most reliable and efficient communication option. However, the relay connection and the UE relay link show better overall spectral efficiency in comparison to the direct link, indicating their ability to transport more data per unit of bandwidth. The option that consumes the least energy among the three is the direct link. The study demonstrates the great potential of D2D communication in emergency scenarios where conventional communication infrastructure may not be available. The direct link is the most dependable and effective alternative for communication, according to the data, although the UE link can still function effectively in the event that the direct link is compromised. The data rate-based method is a useful strategy for finding and choosing D2D partners. The results of this study can direct the development of D2D emergency communication solutions in 5G networks. [ABSTRACT FROM AUTHOR]

In this paper, a low-profile co-linearly polarized simultaneously transmit-receive antenna (STRA) terminal is presented for 5G and upcoming technologies. The proposed STRA terminal comprises of an identical pair of spatially rotated half-circular microstrip antennas for transmission (Tx) and reception (Rx). The challenge of self-interference (SI) is addressed by employing passive SI cancellation techniques such as spatial diversity, field confinement, and surface perturbations. This has been accomplished by using fence-strip structure and V-shaped slots in the ground plane. The STRA was designed, fabricated, and tested for full-duplex operation in a sub-6 GHz band lying from 5.73 to 5.88 GHz, providing high interport isolation ranging from 35.5 dB to a maximum of 46.5 dB. The proposed STRA was implemented using Rogers 3003™ substrate. The measurements yield radiation characteristics with high gain of 5.45-6.0 dBi and 5-6.5 dBi for Tx and Rx antennas, respectively. The measured results are in good conformance with the simulated design. This antenna finds its potential usage in V2X and private 5G networks and can be extended for full-duplex MIMO implementations. [ABSTRACT FROM AUTHOR]

Summary: This work presents a new miniaturized and broadband metamaterial‐inspired U‐slotted patch antenna (MUPA), aiming to cover the full N78 band in the 5G mobile communications. Two techniques as the mushroom metamaterials and U‐slotted patch are synthetically used in the MUPA. A particular MUPA is designed with low‐cost low‐index substrates with εr = 2.2 and further demonstrated in experiments. It is found that the new antenna has an operating bandwidth of 3.30 to 3.82 GHz (14.6%). The patch length is only 18 mm (0.21λ, λ is the wavelength at the center frequency 3.56 GHz). The radiation characteristics of the MUPA are also studied in experiments. The measured antenna gain is 5.54 dBi whereas the cross‐polarizations are successfully suppressed lower than −16 dB, making the MUPA promising to meet the demands of 5G mobile communications. [ABSTRACT FROM AUTHOR]

Flexible textile antennas are important for wireless communication within the expansion of 5G and the Internet of Things (IoT), as it allows for their integration in daily life objects. However, achieving these functionalities in textiles is challenging because of limitations in the electronic performance, flexibility with scalable fabrication process. This paper presents two flexible textile antennas for wearable and non‐ wearable devices compatible with 5G technology created by printing highly conductive silver nanoparticle inks. Two textile substrates are explored, as the dielectric component, a 3D polyester, and a natural origin fabric, burel. The processes used are cost‐effective and scalable, with the antennas designed to operate at 3–3.5 GHz, maintaining their return loss performance even under bending deformation and washing cycles. By transferring the optimized devices into clothes and wall covering, a detailed analysis with experimental measurements of the textile‐based antenna for different operation scenarios is introduced. The work highlights the suitability of these antennas for wearable applications and their alignment with green wireless technologies, contributing to the advancement of sustainable wireless communication systems. [ABSTRACT FROM AUTHOR]

Summary: With the increasing prevalence of wireless sensor networks, the uninterrupted operation of these networks becomes essential. To ensure continuous functionality, wireless networks rely on available base stations (BSs). However, the persistent operation of BSs comes at the cost of substantial energy consumption. Consequently, given the surge in wireless network traffic and the necessity for uninterrupted BS availability, energy efficiency within the BS becomes a concerning issue. To address this, the study employs a semi‐Markov model to depict the availability of the BS, with states corresponding to the failures of its components (baseband unit, remote unit, and software module). The analysis yields a steady‐state solution, with reward rates assigned to each state based on the energy consumption of individual BS components. This approach enables the determination of the expected energy consumption within this model. Additionally, the BS's throughput is assessed using an M/G/1 queueing model with server breakdown. [ABSTRACT FROM AUTHOR]

High‐performance frequency selective surfaces (FSSs) have gained attention for their spatial filtering characteristics in 5G communication systems. In this work, we propose an efficient and accurate design methodology for the FSS. Three different artificial neural network methods (ANN) are employed, and their performances are compared for analysis and synthesis purposes. Results show that GRNN has the highest performance for both training and test phase of ANN based FSS analysis and synthesis. A novel, compact, low‐profile triple band FSS unit cell is introduced, and the working mechanism is described. By applying ANN based design procedure, the unit cell dimensions to resonate at the 5G mm‐wave frequency band is extracted. A unit cell with the extracted physical dimensions is simulated with a full‐wave analysis tool. The simulation results show that the FSS has the filtering feature at the predetermined mm‐wave frequencies of the 5G communication. The prototype of the FSS is fabricated, as well. The simulations are verified experimentally with measurement results. The results show that proposed ANN based analysis and synthesis method can be an effective tool for the design of FSS band‐pass filter for 5G applications. [ABSTRACT FROM AUTHOR]

A variety of fascinating applications, including 5G communication devices, high-speed data transfer, and large-scale Internet of Things (IoT), make life easier with 5G technology. Despite the 5G's superior features, the percentage of electromagnetic (EM) waves in the environment execute a significant increase, unpleasantly. Broadband metamaterial absorbers are an appealing alternative to gather these unwanted signals. This study aims to numerically investigate a broadband metamaterial absorber (MMA) in the 5G high-frequency spectral range with the metasurface formed with coupled resistors. In addition, the 24.25-27.5GHz frequency range, one of the high-frequency 5G bands used by selected countries such as the European Union and China, was preferred. The minor aim of this study is that the usage of coupled elements as resistors may have the ability to increase the absorption bandwidth and magnitude. Comprehensive simulations were performed using the finite integration technique (FIT) utilized by the CST Microwave Studio program to investigate the absorber performance and other relevant parameters. The unit cell design is created metal-substrate-metal structures as asymmetric, single-layer, and easy to implement. The absorption responses are investigated according to the oblique incidence angle, polarization angle for TE &TM modes. The suggested MMA provided an absorbency response above 87.6% in the frequency range 24.20-27.30GHz under normal incidence. Moreover, to comprehend the physical mechanism on absorption, the top and bottom surfaces of the absorber's electric field and surface current distributions are assessed. The designed MMA resulting in relatively high performance and polarization insensitive is helpful for electromagnetic interference (EMI) shielding of 5G signals in the FR2/mmWave frequency regime. [ABSTRACT FROM AUTHOR]

To ensure Energy Efficiency (EE) and better Quality of service (QoS), it is necessary to analyze the energy saving possibilities for low resource utilization in the current networks caused by rigorous QoS requirements and implementing EE approach in the planned model for performance improvement. Distributed Denial of Service (DDoS) attacks aim to exhaust the network's processing and communication capacity by saturating it with packets and generating malicious traffic. There are numerous advantages that make Digital Twin (DT) and Intrusion Detection technique (ID) an effective remedy for a range of (fifth generation) 5G problems. A DDoS attack must be immediately detected and stopped before a legitimate user can access the target of the attacker for the 5G network to provide an efficient energy service. Although they clearly show promise in assisting with the creation and implementation of the challenging 5G environment, Digital Twins is still a relatively new technology for 5G networks but will increase EE. In this research, a thorough examination of the materials was carried out to identify the most cutting-edge DT and ID methods. The purpose of this study was to comprehend the problems with Energy Efficiency, the need for DT, and the methods for dealing with large-scale attack by DDoS on Energy Efficient networks. Only 94 of the 1555 articles produced by the procedure were determined to be relevant using inclusion and exclusion criteria. The outcome demonstrates that in 5G networks, DT, and its fundamental approaches, like QoS and DDoS attack mitigation, can be used to regulate the network's Energy Efficiency. Numerous practical applications focusing on 5G Systems use their own principles. The effectiveness of these strategies was evaluated using several assessment criteria, including DT, Intrusion Detection, QoS, Energy Efficiency, and 5G Systems. Each study issue is thoroughly explained, along with typical methods, advantages, disadvantages, and performance metrics. Energy economy, network reliability, privacy, and cost reduction are all considerably increased by the implementation of intrusion detection technology in 5G systems. The decision is supported by the technology's demonstrated efficacy, scalability, real-time detection capacities, low error level, and personalized learning attributes, all of which contribute to the long-term viability of 5G networks as an entire system. [ABSTRACT FROM AUTHOR]

Novel networking technologies such as massive Internet-of-Things and 6G-and-beyond cellular networks are based on ultra-dense wireless communications. A wireless communication channel is a shared medium that demands access control, such as proper transmission scheduling. The SINR model can improve the performance of ultra-dense wireless networks by taking into consideration the effects of interference to allow multiple simultaneous transmissions in the same coverage area and using the same frequency band. However, scheduling in wireless networks under the SINR model is an NP-hard problem. This work presents a bioinspired solution based on a genetic heuristic to solve that problem. The proposed solution, called Genetic-based Transmission Scheduler (GeTS) produces a complete transmission schedule optimizing size, increasing the number of simultaneous transmissions (i.e., spatial reuse) thus allowing devices to communicate as soon as possible. Simulation results are presented for GeTS, including a convergence test and comparisons with other alternatives. Results confirm the ability of the solution to produce near-optimal schedules. [ABSTRACT FROM AUTHOR]

A compact MIMO antenna has been designed explicitly for Ka-band for 5G wireless networks. The antenna uses four P-shaped radiating patches in E-shaped slots for polarization variety in the 20-40 GHz frequency band. The Rogers RT/duroid 5880 substrate (26 × 25 × 1.6) supports each patch and defective ground for each element. Polarization diversity lowers radiating element interference, making this antenna design advantageous. Therefore, the antenna has a wide bandwidth of 20 GHz. A high isolation level of over -20 dB has been attained by carefully examining the mutual connection between antenna radiators. After a detailed analysis of the radiation patterns, a gain of 17.6 dBi is found. Both total and radiating efficiency exceed 87% and 91%. MIMO system dependability is evaluated by assessing diversity characteristics including ECC, DG, CCL, MEG, and TARC, yielding findings of 0.0035, 9.98 dB, 0.013 bits/sec/Hz, -3 dB, and -10 dB. Simulations and observations show a significant agrement. [ABSTRACT FROM AUTHOR]

The research and innovation related to fifth-generation (5G) networks that has been carried out in recent years has decided on the fundamentals of the smart slice in radio access networks (RANs), as well as the autonomous fixed network operation. One of the most challenging objectives of beyond 5G (B5G) and sixth-generation (6G) networks is the deployment of mechanisms that enable smart end-to-end (e2e) network operation, which is required for the achievement of the stringent service requirements of the envisioned use cases to be supported in the short term. Therefore, smart actions, such as dynamic capacity allocation, flexible functional split, and dynamic slice management need to be performed in tight coordination with the autonomous capacity management of the fixed transport network infrastructure. Otherwise, the benefits of smart slice operation (i.e., cost and energy savings while ensuring per-slice service requirements) might be cancelled due to uncoordinated autonomous fixed network operation. Notably, the transport network in charge of supporting slices from the user equipment (UE) to the core expands across access and metro fixed networks. The required coordination needs to be performed while keeping the privacy of the radio and fixed network domains, which is important in multi-tenant scenarios where both network segments are managed by different operators. In this paper, we propose a novel approach that explores the concept of context-aware network operation, where the slice control anticipates the aggregated and anonymized information of the expected slice operation that is sent to the fixed network orchestrator in an asynchronous way. The context is then used as the input for the artificial intelligence (AI)-based models used by the fixed network control for the predictive capacity management of optical connections in support of RAN slices. This context-aware network operation aims at enabling accurate and reliable autonomous fixed network operation under extremely dynamic traffic originated by smart RAN operation. The exhaustive numerical results show that slice context availability improves the benchmarking fixed network predictive methods (90% reduction in prediction maximum error) remarkably in the foreseen B5G scenarios, for both access and metro segments and in heterogeneous service demand scenarios. Moreover, context-aware network operation enables robust and efficient operation of optical networks in support of dense RAN cells (>32 base stations per cell), while the benchmarking methods fail to guarantee different operational objectives. [ABSTRACT FROM AUTHOR]