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Summary: This article presents a quad element wideband multiple‐input multiple‐output (MIMO) antenna consisting of human face‐shaped patch radiators with defected ground structure (DGS) having rectangular split ring resonator (RSRR) in ground surface. The measured bandwidth of the proposed MIMO antenna is 3.0–6.5 GHz, and the isolation between the ports is more than 16 dB. Additionally, simulated diversity characteristics like the channel capacity loss (CCL), channel capacity (CC), total active reflection coefficient (TARC), mean effective gain (MEG), and envelope correlation coefficient (ECC) are investigated with the measured value and observed to be within the acceptable ranges over the operating frequency band. The suggested antenna can be used in the wireless local area network (WLAN) (i.e., 4.9–5.725 GHz), wireless fidelity (Wi‐Fi) (i.e., 5.15–5.85 GHz), and 5G under 6 GHz (3.3–5.0 GHz) frequency ranges. [ABSTRACT FROM AUTHOR]

The 5G communication network is a promising technology that offers user-centric connectivity to customers, enabling quick, high-capacity, and latency-free access to many applications. Software Defined Networking Controller (SDNC) is an emerging technology that is used for increasing the security and maintaining the dynamic nature of mobile devices in latency and energy-assured 5G wireless communication. Different SDN topology open flow controllers are used in the literature for increasing the throughput and security of the network but they possess some drawbacks such as frequent location update (LU) overhead, high latency, and high energy consumption. This paper proposes a hexagonal software defined network (H-SDN) controller to overcome these challenges. The proposed H-SDN topology is used to preserve Intermediate Message Layer (IML) location during multimedia data transmission. A Core Switch (CS) updates an IML's location within clusters of cells, as long as it remains within the cluster. However, in the proposed method, there will be a location update on the server if the IML departs the cluster. Experiment results show that the proposed method can increase security, which in turn increases throughput, while reduces the location update costs, energy consumption, and transmission latency. [ABSTRACT FROM AUTHOR]

Summary: The emergence of 5G networks has increased the demand for network resources, making efficient resource management crucial. Slice admission control (SAC) is a process that governs the creation and allocation of virtualized network environments, known as "network slices," which can be tailored to meet specific user requirements. However, traditional SAC methods face dynamic and heterogeneous challenges in wireless networks, especially in cloud radio access networks (C‐RANs). To address this issue, machine learning (ML) techniques, particularly deep reinforcement learning (DRL), have been proposed as powerful tools for optimizing SAC. DRL‐based approaches enable SAC systems to learn from previous interactions with the network environment and dynamically adapt to changing network conditions. This review article comprehensively explains the current state‐of‐the‐art DRL‐based SAC, focusing on C‐RANs. The article identifies key challenges and future research directions and highlights the potential benefits of using DRL for SAC, including improved network performance and efficiency. However, deploying these systems in real‐world scenarios presents several challenges and trade‐offs that need to be carefully considered. Further research and development are required to address these challenges and ensure the successful deployment of DRL‐based SAC systems in wireless networks. [ABSTRACT FROM AUTHOR]

This article uses theories of industrial policy to assess the development of China's 5G telecommunications equipment policy. It considers the path China's 5G build-out has taken, and American security concerns in reaction to several nations' potential adoption of China's latest generation of communications equipment. It focuses on several East, South, and Southeast Asian countries and their decisions on whether or not to incorporate China's 5G technology for their networks. It concludes with assessment of future paths in the Sino-US competition over 5G and later generation communications systems adoption. [ABSTRACT FROM AUTHOR]

Short block length "block" codes are typically not used in wireless standards as soft decision decoding is computationally intensive and hard decision decoding results in performance loss. However, short block lengths are of interest to massive machine-type communications (mMTC) and ultra-reliable low-latency communications (URLLC). In this paper, we propose a diversity preserving enhanced hard-decision decoding scheme for parity check codes (PCC) over Rayleigh fading channels. The proposed flip decoding scheme has linear complexity in the block length. Theoretical analysis and simulation results verify the correctness of the proposed detection scheme. [ABSTRACT FROM AUTHOR]

Prediction using computer vision is getting prevalent nowadays because of satisfying results. The vision of Internet of Vehicles (IoV) expedites Vehicle to everything (V2X) communications by implementing heterogeneous global networks. Road crack is one of the major factors that causes road mishaps and damage to vehicles. To ensure smooth and safe driving, avoiding road crack in transportation planning and navigation is significant. To address this issue, we proposed a novel convolutional neural network (CNN)-based smart transportation system. We showed how to quantify the severity of the cracks. We proposed a post-processing algorithm to provide option to the driver to select the safest road toward the destination. The communication system for the proposed smart transportation system has also been introduced. The performance comparison of a few popular CNN architectures has been investigated. Simulation results showed that Resnet50 algorithm provides significantly high accuracy compared with SqueezeNet and InceptionV3 algorithm in order to detect road cracks for the proposed transportation system. We demonstrated high accuracy of measuring the crack severity via numerical analysis. The integration of the proposed system in next generation smart vehicles can ensure accurate detection of road cracks earlier enough providing the option to select alternate safe route toward a destination as advanced driver assistance service. Moreover, the proposed system can also play a key role in order to reduce road mishaps notably by warning the driver about the updated road surface conditions. [ABSTRACT FROM AUTHOR]

This paper addresses the public contestation of the rollout of the fifth generation of mobile telecommunications networks (5G) in the Netherlands. Drawing on Pfaffenberger's framework of technological dramas, we analyze the variety of symbolic expressions about 5G made in documents published by "design constituencies" leading the technology's implementation, "ambivalent intermediaries" reporting on 5G's implementation and its emerging controversial status in the news, and by "impact constituencies" who organize on Facebook to oppose against 5G. The analysis describes a variety of publicly performed narratives and activities that build on symbolic meanings of a supposed public need for 5G, imaginaries of 5G futures, and scientifically manageable and responsible innovation. The paper demonstrates how the technological drama of 5G is constituted by tensions between different interpretations of these publicly performed meanings. However, amidst the drama, meanings of public need and imaginaries of 5G futures are temporarily suspended, constraining the stage for opposition and enforcing partial closure of the conflict. [ABSTRACT FROM AUTHOR]

This article proposes a small multiple-input multiple-output (MIMO) wearable antenna system with four coplanar waveguide-fed antennas operating in the new radio band 79 (4.4–5 GHz) applications. The suggested MIMO antenna system consists of four identical hexagonal-shaped monopole radiators, and each is printed on polymide substrate with the size of 1.33 λ0 × 1.03 λ0, where λ0 is the wavelength at centre frequency 4.5 GHz. By placing four antenna elements in orthogonal arrangements, independent radiation pattern is achieved, thereby increasing isolation better than 17 dB. Specifically, no dedicated mechanism has been introduced to obtain the substantial isolation. All the antenna elements in the MIMO arrangement have broadband operation resonating between 4.4 and 5 GHz covering n79 (new radio band) 5G applications. The proposed antenna has a peak gain around 3.8–4 dBi over the operating frequency with radiation efficiency ranging from 88% to 90%. Since flexible substrate is used in the design, conformability of the antenna has been verified by performing bending analysis. The MIMO antenna provides better measured results, which are consistent with the simulated results; therefore, the antenna explored in this research could be the better candidate for 5G conformal and wearable applications. [ABSTRACT FROM AUTHOR]

Choosing polymers as antenna substrates has become a significant challenge, as it involves addressing the escalating demands of emerging 5G applications for bandwidth and data transfer, while simultaneously prioritizing environmental adaptability. Furthermore, various applications such as IoT and smart wearables utilize specific frequency bands, such as sub-6 GHz, millimeter waves (MMwaves), and terahertz, which are characterized by unfavorable conditions of propagation. The current in-depth study focuses on the exploration of two specific polymers, Polymethyl methacrylate (PMMA) and Polydimethylsiloxane (PDMS), as potential substrates for designing flexible microstrip antenna operating at 5.8 Ghz. The proposed antenna showcases a compact design, measuring 25.6 × 45.6 × 2.2 mm3 for PMMA and 20.2 × 40.2 × 2.2 mm3 for PDMS. Notably, with a consistent substrate thickness of 2.2 mm, the PMMA polymer outperforms PDMS, achieving a higher gain of 4.4dBi compared to PDMS's gain of 3.75dBi. Furthermore, both substrates exhibit improved performance under bending conditions and excellent impedance matching, it is worth that in both cases, the return loss remains under 22 dB. This comprehensive analysis firmly establishes the viability of PMMA and PDMS in delivering efficient flexible microstrip antenna performance, thereby contributing significantly to the advancement of IoT devices technology and design within the Sub-6 GHz frequency band. [ABSTRACT FROM AUTHOR]

Fifth generation new radio (5G NR) is bringing revolutions in almost every field such as healthcare, industrial automation, smart farming, and defense. These fields utilize three major use case scenarios of 5G NR viz. eMBB, URLLC, and mMTC. 5G NR deployment relies on two major frequency bands such as sub-6 GHz and high-frequency bands (millimeter waves). Among all sub-6 GHz bands, the n78 band (3300–3800 MHz) is gaining popularity due to its unique characteristics viz. higher capacity and coverage, wide bandwidth, and higher data rate. Despite these unique characteristics, in the 5G standalone architecture, users expect high-speed video/voice transmission without delay and good quality of services (QoS) requirements. QoS is one of the important paradigms that indicates the quality of services experienced by end users instead of services claimed by service providers. In this work, we have designed a QoS scenario that utilizes the n78 band with an "urban macro mixed office scenario with low loss" path loss model. As per types of services are concerned, the scenario utilizes six different traffic templates (i.e., FTP, Voice, Video, COAP, CBR, and Email). The path loss model operates on non-line-of-sight scenarios with Rayleigh fading and eigen beamforming using 64 × 32 antenna elements. The performance of the proposed scenario is examined through different metrics i.e., throughput, packet drop ratio, and delay. Here, priorities to different traffic templates are assigned based on GBR and non-GBR resource types. In addition, the proportional fair scheduling algorithm is employed to schedule the resources. It was observed that video services achieved a higher throughput of 25.93 Mbps due to their prioritization in the QoS model. Conversely, FTP services experienced higher delay, measured at 64 ms, and a packet delivery ratio of 5.94%. [ABSTRACT FROM AUTHOR]

In this paper, a planar of small size Tapered slot Vivaldi antenna for mm‐Wave 5G application is proposed. The main goal can be presented by designing of a small size antenna with good performance antenna for mmWave and massive MIMO applications. The suggested antenna structure is portrayed by a size of 6.4 × 6 × 0.254 mm3 printed on a dielectric substrate (Roger/RT Duroid −5880) with εr = 2.2, and tanδ = 0.0009. The antenna displayed a small size and good performance with an impedance bandwidth equals 17.9 GHz ranging from 22.1 GHz to 40 GHz with the value of S11<−10 dB, which covers all mm‐Wave frequency bands. The antenna gain is found fluctuating from 6.2 dB up to 7.1 dB in the whole band, which the maximum gain value is found at 22.1 GHz. The radiation of the antenna is found the end‐fire type. The HFSS software package was used to design and simulate the proposed antenna structure. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Summary The presented state of the art is a novel coplanar optically transparent antenna designed to operate in extended GSM, L‐band, and UWB applications for vehicular communication. The presented radiator operates using a coplanar waveguide feed mechanism without a separate ground plane layer with a minimal conductive surface to enhance the transparency of the proposed antenna. The proposed antenna design has dimensions of 40 × 20 mm2, and a transparent material of soda–lime glass is used as a substrate with a dielectric constant of 7. The radiating element over the substrate is the conductive film fluorine‐doped tin oxide (FTO) with a sheet resistance of 7 Ω/sq. The operating frequency range of the designed antenna is from 0.86 to 14.45 GHz, which encloses the E‐GSM (900 MHz), L‐band (1–2 GHz), and UWB (3.1–10.6 GHz) frequencies. The peak gains at the operating frequencies are 1, 1.6, and 4.34 dBi, respectively. The designed antenna is fabricated and measured, and the performance metrics are plotted and compared. Since the transparent antenna is designed, the tendency of a substance to conduct light is measured as the optical transmittance, and it is calculated as 95% in the glass reference and 82% in the air reference. [ABSTRACT FROM AUTHOR]

In this article, we propose a distributed synchronization solution to achieve decentralized coordination in a system of collaborative robots. This is done by leveraging cloud-based computing and 5G technology to exchange causal ordering messages between the robots, eliminating the need for centralized control entities or programmable logic controllers in the system. The proposed solution is described, mathematically formulated, implemented in software, and validated over realistic network conditions. Further, the performance of the decentralized solution via 5G technology is compared to that achieved with traditional coordinated/uncoordinated cabled control systems. The results indicate that the proposed decentralized solution leveraging cloud-based 5G wireless is scalable to systems of up to 10 collaborative robots with comparable efficiency to that from standard cabled systems. The proposed solution has direct application in the control of producer–consumer and automated assembly line robotic applications. [ABSTRACT FROM AUTHOR]

Streaming data are present all around us. From traditional radio systems streaming audio to today's connected end-user devices constantly sending information or accessing services, data are flowing constantly between nodes across various networks. The demand for appropriate outlier detection (OD) methods in the fields of fault detection, special events detection, and malicious activities detection and prevention is not only persistent over time but increasing, especially with the recent developments in Telecommunication systems such as Fifth Generation (5G) networks facilitating the expansion of the Internet of Things (IoT). The process of selecting a computationally efficient OD method, adapted for a specific field and accounting for the existence of empirical data, or lack thereof, is non-trivial. This paper presents a thorough survey of OD methods, categorized by the applications they are implemented in, the basic assumptions that they use according to the characteristics of the streaming data, and a summary of the emerging challenges, such as the evolving structure and nature of the data and their dimensionality and temporality. A categorization of commonly used datasets in the context of streaming data is produced to aid data source identification for researchers in this field. Based on this, guidelines for OD method selection are defined, which consider flexibility and sample size requirements and facilitate the design of such algorithms in Telecommunications and other industries. [ABSTRACT FROM AUTHOR]

This paper presents a wideband low-profile dual-polarized patch antenna with helical-shaped L-probe feeding (HLF) for mmWave 5G mobile device applications. Parametric studies on the HLF structure are performed to identify the optimal specifications. As a result, the optimized antenna achieves a wide bandwidth of 5.4 GHz (24.2–29.6 GHz), good isolation > 18 dB between ports, and 5.1 dBi of good peak realized gain, which is experimentally verified with a 10× upscaled antenna. In addition, various one × four phased arrays with different port configurations and beamform capabilities are designed and simulated for the peak realized gain. The designed antenna array shows a high peak realized gain of 10 dBi, high isolation of 15 dB between the ports, and a small substrate thickness of 0.048λ0 (λ0 is the wavelength of 24.25 GHz). Compared to the state-of-the-art antennas, the designed dual-polarized antenna can operate in the frequency ranges of 24.25–29.6 GHz, including n257, n258, and n261 of the 5G new radio frequency range 2. [ABSTRACT FROM AUTHOR]

The digitalization of agriculture is rapidly changing the way farmers do business. With the integration of advanced technology, farmers are now able to increase efficiency, productivity, and precision in their operations. Digitalization allows for real-time monitoring and management of crops, leading to improved yields and reduced waste. This paper presents a review of some of the use cases that digitalization has made an impact in the automation of open-field and closedfield cultivations by means of collecting data about soils, crop growth, and microclimate, or by contributing to more accurate decisions about water usage and fertilizer application. The objective was to address some of the most recent technological advances that are leading to increased efficiency and sustainability of crop production, reduction in the use of inputs and environmental impacts, and releasing manual workforces from repetitive field tasks. The short discussions included at the end of each case study attempt to highlight the limitations and technological challenges toward successful implementations, as well as to introduce alternative solutions and methods that are rapidly evolving to offer a vast array of benefits for farmers by influencing cost-saving measures. This review concludes that despite the many benefits of digitalization, there are still a number of challenges that need to be overcome, including high costs, reliability, and scalability. Most of the available setups that are currently used for this purpose have been custom designed for specific tasks and are still too expensive to be implemented on commercial scales, while others are still in their early stages of development, making them not reliable or scalable for widespread acceptance and adoption by farmers. By providing a comprehensive understanding of the current state of digitalization in agriculture and its impact on sustainable crop production and food security, this review provides insights for policy-makers, industry stakeholders, and researchers working in this field. [ABSTRACT FROM AUTHOR]

Summary Delivering health care services in isolated rural regions through vehicular communications has recently attracted more attention. Real‐time video streaming is one of the most commonly used applications in such services. Escorting this increasing interest, there is a high demand for high‐quality streaming video in vehicular environments. However, these services face challenging network characteristics such as high dynamic topology and mobility, leading to high packet loss and degraded visual quality. This paper presents a smart approach to multi‐access terrestrial and non‐terrestrial networks (NTNs) for high‐quality and real‐time video streaming in vehicular environments to enhance healthcare services in remote areas. The proposed approach integrates a mobile telemedicine unit connected to an expert site through different channels, including satellite communication, 5 Generation (5G), and long‐term evolution (LTE) networks. A modified multipath QUIC extension (MPQUIC) was introduced to stream data hybridly through the network. Furthermore, multiple description coding (MDC) was applied to split data into two different descriptions and prioritize one over the other. Important data would be transmitted through cellular networks, and non‐priority data would be transmitted through satellite links, enhancing the reliability of video transmission. We demonstrate the effectiveness of our approach through the use of a connected ambulance as a case study. The Mininet‐Wifi was used to emulate network conditions. The peak signal‐to‐noise ratio (PSNR), structural SIMilarity (SSIM), and video multimethod assessment fusion (VMAF) were measured to evaluate the received video quality; the received data rate and packet loss were also calculated. The obtained results show our proposed method's efficiency by reducing latency by up to 60% and improving the receiving data rate by up to 143% compared with the classical MPQUIC. The proposed system enhances video quality by up to 70%. It minimizes packet loss by up to 50% compared with the unreliable QUIC, showcasing the potential to improve m‐health services' efficiency and mobility in isolated rural regions. [ABSTRACT FROM AUTHOR]

C-RAN (Cloud Radio Access Network) is a 5G architecture that consists of sites and three-layer Data Centers (DCs), which include the central office DC, local DC, and regional DC. Network slicing, which enables infrastructure providers (InP) to create independent logical networks, is essential in this architecture. By utilizing this technology, InPs can maximize the utility of the network by providing slices to service providers in response to their slice requests. However, almost all of the recent research on slice admission control (SAC) schemes has only considered one or two layers of DCs, which limits the efficiency of the slicing process and decreases network utility. To address these issues, this paper proposes an intelligent SAC scheme called ISAC that considers all three-layer DCs. Instead of relying on reinforcement learning algorithms like Q-learning, which are effective in discrete environments with limited state space but give poor performance in continuous environments, ISAC employs the Approximate Reinforcement Learning (ARL) algorithm. ARL is better suited for 5G network modeling because it can adapt to continuous environments, allowing for a more accurate representation of the underlying physical processes. Extensive simulation studies demonstrate that ISAC significantly improves performance in terms of slice request rejection rates, InP revenue, accepting more slices, and optimizing resource utilization. [ABSTRACT FROM AUTHOR]

The growing need for applications with low latency and high bandwidth in 5G networks has shifted the emphasis towards integrating edge computing into mobile network architectures. The optimal deployment of edge servers (ESs) is crucial for balancing performance and cost. Current research primarily focuses on the optimal deployment of ESs. However, there is limited attention on forecasting the workload of ESs, particularly in scenarios where they are placed in their optimal positions, which is crucial for accommodating anticipated variations in user densities and workload fluctuations expected in the near future. This research forecasting of workload in 5G networks by leveraging the Temporal Hierarchical Attention Mechanism Network (THAMNET) model for accurate Internet traffic forecasting. Addressing this gap, the Max–Min Fairness Allocation Scheme (MMF-AS) algorithm is implemented to ensure a balanced workload distribution. This approach facilitates fair allocation of Base Stations (BSs) to ESs, taking into account factors such as workload, distance, and connectivity. A novel approach is introduced by integrating the THAMNET forecasting model with the Particle Swarm Optimization (PSO) and MMF-AS algorithms. The proposed method considers predicted future traffic demands, and connectivity between ESs and BSs, and aims to achieve balanced workload distribution, higher utilisation rates, minimised latency, and reduced energy consumption. Experimental results demonstrate equitable workload distribution 25.95%, utilisation rate 17.57%, and notable reductions in latency 47.61% and energy consumption 32.28% compared to the non-forecasting comparison. [ABSTRACT FROM AUTHOR]

In this research, we explain comprehensive industrial and innovation results on using an artificial neural network (ANN) method to improve the performance of microstrip patch antennas for 5G, indoor-outdoor, and Ku band uses. To determine if an antenna is appropriate, this article discusses multiple methods, one of which is to do a simulation using validating software like high frequency structure simulator (HFSS) and Altair Feko. Based on the Rogers RT 5880 substrate, the antenna is constructed. There is a loss tangent of 0.0009 and its dimensions are 17.1053 mm in length and 16 mm in width. Its dielectric constant is 2.2. Despite its small size, it boasts an impressive maximum efficiency of almost 90% and a gain of approximately 8 dB. As an indicator of ANN model performance, we may look at the R-squared value (99%), the mean square error (MSE), which is approximately 0.0015, and the confidence interval (99%). The ANN models are the most accurate and have the lowest error rate when it comes to predicting efficiency and gain. The suggested antenna is a promising contender for the targeted Ku band, indoor/outdoor, and 5G uses, as verified by the clustering of computer simulation technology (CST), HFSS, and Altair Feko simulated results with the measured and predicted outcomes of ANN approach. [ABSTRACT FROM AUTHOR]

This comprehensive article explores the massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, cell-free MIMO, and security considerations, this article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights the challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of federated learning in M-MIMO systems. By examining these cutting-edge developments, this article aims to advance knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks. [ABSTRACT FROM AUTHOR]

This paper introduces a dual-feed substrate integrated waveguide antenna design with a modified H-Slot (DFH-SIW) for Ka-band 5G applications. In general, 5G base stations operating in Ka-band applications need large bandwidth-based antennas with high gain to solve the problem of path loss and high data capacity. To resonate with an ideal bandwidth at 28/38 GHz, this study proposes a high-gain antenna with a modified H-slot. This study used the CST EM tool to design the proposed antenna model and evaluate and optimize its characteristics. The proposed dual feed antenna has compact dimensions of 12×12×1.2 mm and was constructed on a Roger 5880 substrate with an appropriate permittivity of 2.2 and a minimal loss tangent of 0.0009. The proposed dual-feed antenna showed an ideal reflection coefficient of less than -10dB and a bandwidth of 3.7 GHz and 3.23 GHz at operating frequencies of 28 and 38 GHz, respectively. The proposed design operates at the 28 GHz frequency with 73.2% efficiency and 4.3 dBi gain, and at 38 GHz with 83.68% efficiency and 6.7 dBi gain. This antenna is intended to be used in future 5G wireless networks and has outstanding overall performance in terms of return loss, gain, and wide bandwidth. [ABSTRACT FROM AUTHOR]

Combining Intelligent Reflecting Surfaces (IRSs) with Non-Orthogonal Multiple Access (NOMA) effectively enhances communication. This study introduces a NOMA-assisted Downlink Transmission (DT) system, emphasizing Energy Efficiency (EE) optimization. EE, crucial in Wireless Communications (WCs), measures data transmission relative to energy consumption. This study focuses on a Deep Deterministic Policy Gradient (DDPG) algorithm that intelligently adjusts IRS phase-shift matrices and access point beamforming in NOMA DT. Beamforming directs signals to users for optimal strength and quality, while phase shift control enhances signal coverage and quality. Strategic IRS placement improves user signal transmissions. The simulation results demonstrate significantly improved EE compared to other algorithms, such as Deep Q Network (DQN) and Proximal Policy Optimization (PPO), showcasing the effectiveness of the combined IRS and NOMA approach in enhancing communication systems' EE. [ABSTRACT FROM AUTHOR]

In this work, the design and implementation of a high-gain Hexagon Loop Antenna (HLA) for 5G and WLAN application is presented. Initially, a hexagon patch was designed to resonate at 3.5 GHz. A loopbased radiator was tailored to obtain miniaturization without affecting the overall performance of the proposed antenna. A CPW feed was utilized to maintain the wide bandwidth with improved return loss. FR-4 material was used as a dielectric to retain the low cost of the antenna. The return loss was kept well below -10 dB, from 3.2 GHz to 6.4 GHz. The gain of the proposed Microstrip Hexagon Loop Antenna (MHLA) is 5.3 dBi at 3.5 GHz and 8.2 dBi at 5.8 GHz, respectively. To improve the gain and directivity of the proposed antenna, a square-shaped AMC unit cell was considered, and finally, a [4×4] ground plane AMC was integrated with the antenna. The radiation pattern of the antenna is stable and low crosspolarization is maintained for the desired band. A simulation of the proposed antenna was carried out in the ANSYS HFSS tool and the experimental results were measured inside an anechoic chamber. The experimental and simulated results of the proposed antenna are in good agreement. Its simple and lowprofile structure, lower cost, and high gain ensure that the proposed high gain antenna is well suited for sub-6 GHz band and wireless application. [ABSTRACT FROM AUTHOR]

This research explores the interplay between innovation, economic systems, governance structures, and law, and how they interact with one another in the context of China and Ethiopia's investments in the Digital Silk Road. The way cutting-edge methods related to governance and economic systems might help lower the risks involved in major infrastructure projects, like the Digital Silk Road, particularly in light of law and 5G developments, is investigated. China–Africa connections are to be strengthened, sustainable development is to be encouraged, and healthy economic progress is the goal of the partnership between Ethiopia and the Hainan Free Trade Port. The impact of these transnational investments on fair growth and sustainable development is assessed, while exploring the evolving agendas and procedures governing investments. This research draws attention to how the law and legal cooperation between Ethiopia and China may promote mutually advantageous outcomes, promote transparency and governance mechanisms, and lessen the likelihood of disputes. This research on the factors influencing the future of the Digital Silk Road and its consequences for long-term, sustainable economic growth, and business in the area, aims to provide valuable insights for policymakers, development professionals, and academics, and for the copromotion of China and Ethiopia in terms of digital investment. This research relates to the promotion of the African Continental Free Trade Area (AfCFTA), in terms of construction and economic development. It also examines how the DSR raises concerns about data security and privacy, cross-border transactions, technology transfer, and cyberterrorism, as well as encourages digital investment, such as through enhancing digital governance regulations, modernizing international investment agreements (IIAs), and bolstering global health, coordination, and cooperation; the article concludes by analyzing the implications for Africa. The findings show that such cooperation would support Africa's digital transformation and sustainable development, while strengthening China–Africa cooperation. [ABSTRACT FROM AUTHOR]

Harnessing remote computation power over the Internet without the need for expensive hardware and making costly services available to mass users at a marginal cost gave birth to the concept of cloud computing. This survey provides a concise overview of the growing confluence of cloud computing, edge intelligence, and AI, with a focus on their revolutionary impact on the Internet of Things (IoT). The survey starts with a fundamental introduction to cloud computing, overviewing its key parts and the services offered by different service providers. We then discuss how AI is improving cloud capabilities through its indigenous apps and services and is creating a smarter cloud. We then focus on the impact of AI in one of the popular cloud paradigms called edge cloud and discuss AI on Edge and AI for Edge. We discuss how AI implementation on edge devices is transforming edge and IoT networks by pulling cognitive processing closer to where the data originates, improving efficiency and response. We also discuss major cloud providers and their service offerings within the ecosystem and their respective use cases. Finally, this research looks ahead at new trends and future scopes that are now becoming possible at the confluence of the cloud, edge computing, and AI in IoT. The purpose of this study is to demystify edge intelligence, including cloud computing, edge computing, and AI, and to focus on their synergistic role in taking IoT technologies to new heights. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) mobile networks offer flexibility to address various emerging use cases. Radio virtualization enhances flexibility by enabling multiple heterogeneous virtual radios to coexist on the same hardware. One method for virtualizing radio devices involves using virtual machines and containers to multiplex software radio implementations over generic multipurpose radio hardware. This paper reviews security issues in this context, evaluates the experimental bounds of communication for software-defined radio (SDR) devices, and assesses virtualization's impact on radio virtualization's performance. This study aims to determine the suitability of virtual environments for SDR applications. The results indicate that container-based radio virtualization performance is comparable to SDR applications running on native Linux. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) is perceived as one of the most popular wireless transmission candidate in the last decade however due to ever-increasing current generation bandwidth demands; it becomes incompetent to fulfil the requirements. A futuristic and high speed data transmission technique is replacing RF nowadays i.e. Free space optical communication (FSOC) because of its great potentials. Future generation communication systems require competent FSOC technology to sustain wireless traffic in 5G and 6G services. Because the features of FSOC and RF are complimentary, combining the two technologies is seen as a potential way to enable future communication systems. Hybrid RF/FSOC is a good way to overcome the limits of separate systems while still taking use of the beneficial aspects of each technology. Wireless systems use e.g. in hybrid RF/FSOC can increase individual network performance in terms of performance, dependability, and economical operations. In this work, a detailed review on FSOC systems is presented by doing the extensive literature review of reported research. Review covered key ideas consisting all sorts of FSOC systems, FSOC design with multiple and single beams, as part of the evaluation. The examination of rainfall and hazy effects on FSO signal transmission is also included in the review. The key benefits, future potential, and obstacles that must be addressed in order to successfully implement FSOC for 5G paradigms are presented. [ABSTRACT FROM AUTHOR]

In the ever-evolving landscape of wireless communication systems, including fifth-generation (5G) networks and beyond (B5G), accurate Modulation and Coding Scheme (MCS) prediction is crucial for optimizing data transmission efficiency and quality of service. Traditional MCS selection methods rely on predefined rules and heuristics, offering transparency and control but lacking adaptability in changing wireless conditions. The emergence of Machine Learning (ML) has brought transformative capabilities, particularly in MCS prediction. ML leverages data-driven models, promising improved accuracy and adaptability in dynamic wireless environments. This paper marks a novel endeavor in this domain, as it explores and evaluates a range of machine learning (ML) techniques for predicting MCS in orthogonal frequency-division multiplexing (OFDM) systems, representing the first such investigation in this field. Additionally, it introduces a specialized Deep Neural Network (DNN) architecture with two hidden layers for MCS prediction, guided by performance metrics such as accuracy, precision, recall, and F1-score. The examined ML methods include Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF), and Bagging with k-NN (B-kNN). These methods undergo thorough training and evaluation using a dataset generated from simulations of non-standalone 5G networks. The study incorporates physical layer measurements and employs a ray-tracing path loss prediction model for comprehensive environmental characterization. Also, advanced data mining techniques preprocess raw data, addressing model underfitting and overfitting challenges. Finally, performance evaluation results reveal that the ANN with two hidden layers achieves the highest accuracy at 98.71%, while RF and B-kNN methods attain the lowest accuracy, below 88.65%. SVM and ANN models, with one and four hidden layers, respectively, demonstrate comparable MCS prediction accuracy, ranging from 97.02 to 97.30%. [ABSTRACT FROM AUTHOR]

This article presents three efficient rectifiers for radio frequency energy harvesting (RFEH) systems operating at the fifth generation (5G) band (3.5 GHz). Each rectifier operates at various input power levels (high, low, and across a wide power range). The high and low-power rectifiers feature a single serial topology using HSMS-2860 and SMS-7630 Schottky diodes, respectively, along with microstrip lines to implement the input and output filters and the impedance matching network. At an radio frequency (RF) power level of 15 dBm, the high-power rectifier harvests 67.4% to direct current (DC) power with a 300 Ω load resistor and an output voltage of 2.5 V. The low-power rectifier achieves its maximum power conversion efficiency (PCE) at -2 dBm, reaching 45% efficiency with a 1,200 Ω load. The rectifier with a extended input power range comprises two branches of subrectifiers functioning at both high and low power levels. Depending on the power level, the considered subrectifier harvests radio frequency power into DC power, while the other subrectifier is deactivated. Across a power span of 32.5 dB (ranging from -13 to 19.5 dBm), the rectifier maintains an efficiency above 30%. The proposed rectifiers are efficient and suitable for implementation in 5G-enabled RFEH systems. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a compact (20 × 20 × 1.59 mm3), (0.34λg × 0.34λg × 0.01λg at 2.4 GHz) triple band monopole antenna for Internet of Things (IoT) applications. The geometry of the antenna consists of (i) U‐shape monopole with feed line, (ii) stubs, and (iii) modified ground to achieve three independent operating bands ranging from (i) 2.4–2.48 GHz for industrial, scientific, and medical (ISM)/3G; (ii) 3.4–3.6 GHz for 4G/5G; and (iii) 5.725–5.825 GHz for 5.8G Wi‐Fi/extended 5G. Various parameters, input impedance, and current distribution of the proposed structure are carried out to investigate the effects of stub, ground plane and analyze the radiation. The measured result covers the three individual bands in range of 2.38–2.48 GHz, 3.41–3.61 GHz, and 5.76–6.04 GHz, respectively, and exhibits stable omnidirectional radiation patterns, acceptable antenna gain, and efficiency in the operating bands. The experimental result of the fabricated antenna closely matches with the simulated result. Therefore, satisfactory result ensures its ability to work for 3G/4G/5G/extended 5G IoT portable applications. [ABSTRACT FROM AUTHOR]

In order to investigate and analyze the behavior of 4G and 5G OFDMA cellular networks in real time, it is essential to have a real‐time testbed to emulate these cellular networks. We developed the experimental testbed in this work and proposed a real‐time approach to emulating these networks. We take real‐time measurements in indoor and outdoor environments. From the results, we say the proposed testbed can be used to identify the activity of spectrum occupancy of 4G and 5G cellular systems within a specified time, and one can also test their algorithm, protocols, and solutions using our developed testbed. [ABSTRACT FROM AUTHOR]

Summary: An evaluation of various transmit precoding schemes is proposed in this thesis on basis of spectral efficiency (SE) of massive MIMO (m‐MIMO) system in 2 GHz spectrum. The present generation of wireless networks must be rethought due to the rapidly rising user base, huge volume data transfer, wide coverage requirement, and exponential rise in data rate. 5G mobile network includes a multi‐fold increase in network capacity, energy conservation, decreased latency, higher coverage probability, and a seamless connection. m‐MIMO has provided good solution for enhancing the data rate with the coverage, overcoming the effects of multipath fading and has also increased diversity of the system. Massiveness of MIMO system along with 5G network is the key technology to address the issue of SE, throughput, improvement of QoS (quality of service), coverage probability, power delay profile, diversity simulation, energy efficiency, and improvement in bit error rate. Parameters such as SE, throughput, and coverage probability are important for any communication system, and their improvement can increase overall capacity of cellular network system and could meet the requirement of upcoming demand for mobile network. The research paper is focused on performance analysis of m‐MIMO with reference to the SE of various transmit precoding schemes. Simulation results show that SE provided by M‐MMSE (multi‐cell minimum mean‐squared error) technique of precoding ranks highest for the same number of antennas and pilot reuse factor as compared to other schemes. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) and 5G communication technologies in smart cities deliver promising services for heterogeneous applications. The application reliability banks on uninterrupted and seamless services experienced by the users. However, the increasing smart city application demands influence the experience reliability through augmented wait times. This article therefore introduces a Coherent Reliability Service Broadcasting Technique (CRSBT) for sustaining constructive application services. This technique incorporates linear regressive and digressive learning for application service improvements and restrictions. Based on the demand, the regressive process verifies the wait time and with the reducing demands, the service broadcast ratio is verified. These two factors are verified post the demand and response through 5G resource allocations and IoT computations. Both the service-oriented features are validated for regressive service broadcast and either of the one is used for digressive response. The coherence between the computations (IoT) and resources (5G) is verified on-demand and linearly. Therefore, the proposed technique is reliable in sustaining service broadcast, less wait time, and maximum flexibility. [ABSTRACT FROM AUTHOR]

One of the main sources of information dissemination is social networks. Changes in social and Internet of Things (IoT) relationships can affect the quality of service (QoS) of device-to-device (D2D) communication in fifth-generation (5G) networks. Integration of social networks and IoT networks will allow users to improve their communication abilities with proximity users. The most challenging issues are interference and channel uncertainty due to massive connectivity and random movement of users in an urban dynamic environment. In this paper, D2D-based social Internet of Things (D2D–social IoT) in a 5G network is modeled for urban regions. To address these issues, we formulate a throughput maximization problem under the maximum power and QoS constraints. The problem is divided into multiple subproblems to reduce interference and enhance throughput. First, we leverage the interference channel link for intelligent resource sharing with better QoS by the spatiotemporal method. The second one involves bisection-based power search optimization by utilizing the Mellin transformation method for latency and power minimization. Simulation results demonstrate that the proposed method significantly improves the network performance in terms of throughput, sum rate, and reduction in network latency by up to 19.91%, 26.24%, and 31.57%, respectively. It is expected that an inclusive implementation of the said method can enable resource allocation in 5G-enabled social IoT networks for the development of smart city. [ABSTRACT FROM AUTHOR]

Beamforming using highly directional antennas is inevitable to compensate the propagation losses and enable communication in the millimeter wave (mmWave) band. However, this directivity makes mmWave links fragile and sensitive to environment dynamics and blockage. Consequently, initial access and management of the mmWave links in dynamic environments turns to be a big challenging issue, especially in dense network scenarios. In particular, a massive amount of beamforming training (BT) overhead with high delay is needed to establish the mmWave link between a user device (UD) and the deployed small cells (SCs). The consequences are become more severe in case of mobility, since frequent handovers (HOs) between different beams/SCs is needed to preserve the connection with moving UDs. Inspired by the fact that directionality makes the mmWave communications to be geometry and location driven, this paper proposes a geometry-based schemes for the initial access and management of mmWave links. In the proposed schemes, geometric information of the target area including the UDs locations, SCs coordinates and the target area maps are exploited to alleviate the complexity of the exhaustive-based BT. The high impact of the proposed mmWave link initial access and management schemes over the conventional ones in different terms such as BT complexity and total energy consumption rates is proved via simulation analysis. [ABSTRACT FROM AUTHOR]

Butler Matrix networks are well established as beamforming networks for phased antenna arrays. The challenge we address in this work is to cover the entire (advanced 5G or 6G) FR3 band (7–24 GHz) with a single network, while retaining low losses and minimal size. The employed multilayer topology is also well established; however, the matching between the utilized hybrid couplers and the phase shifters constitutes a major challenge for such a wideband operation. This is achieved herein by employing meander lines with appropriate curvature and introducing two distinct design methods for the Butler Matrix. The first method focuses on designing individual components separately, followed by their integration into the overall Butler Matrix structure. This approach is demonstrated through the design, prototyping, measurements, and validation of an 8 × 8 Butler Matrix beamformer, which operates across the 6–16 GHz band (FR3 Low). The second method introduces a wideband-matching technique which simplifies the implementation process by designing the Butler Matrix as a single, unified structure. This technique is applied to both 4 × 4 and 8 × 8 Butler Matrices, which are implemented and simulated for the low FR3 band. Both design methods result in wideband operation and compact size and meet the desired performance criteria. [ABSTRACT FROM AUTHOR]

A high-tuning range frequency reconfigurable dual-band compact cylindrical Dielectric Resonator Antenna (DRA) for 5 G Sub 6 GHz applications is presented in the proposed work. The work presented here provides compactness, frequency reconfigurability (FR), and dual-band. FR is obtained through two PIN diode switches, which operate in ON-ON, ON-OFF, OFF-ON, and OFF-OFF configurations and offer a maximum wide tuning range and a total spectrum of 44.44% and 71.49%, respectively. In the cylindrical DRA, the ${\rm{HE}}{{\rm{M}}_{11{\rm{\delta }}}}$HEM11δ and ${\rm{HE}}{{\rm{M}}_{12{\rm{\delta }}}}$HEM12δ modes create dual-band, while the hybrid structure and higher order mode excitation yield compactness. [ABSTRACT FROM AUTHOR]

The Next-Generation Networks offer a green environment with demanded data rates with ultra-low latency. Future efforts will be oriented in more degrees of freedom and system complexity with incorporating global optimization in terms of non-linearities, cost-effective, and reduced environmental impacts. The multitone upconverted radio over fibre (RoF) link with an optical modulator as phase modulator as desired alternatives with respect to optimization features and quantum photonic integration. In this paper, a framework has been developed to characterise the upconverted phase modulated signal model based on next-generation networks, in which an analytical model is investigated for single-tone upconverted, two-tone upconverted, and three-tone upconverted. Numerical simulations have been carried out to verify the novel outcomes using OptSIM software. The developed analytical models have a major contribution to the implementation of next-generation networks such as 5G, 6G, WiMAX, Quantum Communication, etc. The fundamentals of harmonics and the intermodulation product terms of third and fifth order via optical link are also evaluated for multitone Phase modulated RoF link with upconversion method. As per the finding outcomes, the proposed link is adaptable with frequency upconversion and long fibre distances. [ABSTRACT FROM AUTHOR]

Summary: Network architects and engineers face challenges in meeting the increasing complexity and low‐latency requirements of various services. To tackle these challenges, multi‐access edge computing (MEC) has emerged as a solution, bringing computation and storage resources closer to the network's edge. This proximity enables low‐latency data access, reduces network congestion, and improves quality of service. Effective resource allocation is crucial for leveraging MEC capabilities and overcoming limitations. However, traditional approaches lack intelligence and adaptability. This study explores the use of deep reinforcement learning (DRL) as a technique to enhance resource allocation in MEC. DRL has gained significant attention due to its ability to adapt to changing network conditions and handle complex and dynamic environments more effectively than traditional methods. The study presents the results of applying DRL for efficient and dynamic resource allocation in MEC Computing, optimizing allocation decisions based on real‐time environment and user demands. By providing an overview of the current research on resource allocation in MEC using DRL, including components, algorithms, and the performance metrics of various DRL‐based schemes, this review article demonstrates the superiority of DRL‐based resource allocation schemes over traditional methods in diverse MEC conditions. The findings highlight the potential of DRL‐based approaches in addressing challenges associated with resource allocation in MEC. [ABSTRACT FROM AUTHOR]

This research work analyzes economic alternatives for the provision of ultra-reliable low latency communication (URLLC) and enhanced mobile broadband (eMBB) services by mobile network operators over the same fifth-generation (5G) network. Two business models are proposed to provide the two services to end users. Concretely, a monopoly is a single operator who offers both services, and a duopoly is two different operators that share network resources and offer one service each. In addition, two types of network scenarios for resource sharing are studied. Specifically, a shared network (SN) is a type of network scenario allowing resources to be shared between the two services without priority. A differentiated network (DN) is a type of network scenario that allows resources to be shared between the two services with a priority to URLLC service using network slicing (NS). Regarding the economic aspects, the incentive is modeled through the user’s utility and the operator’s benefit. At the same time, game theory is used to model the strategic interaction between users and operators, and queuing theory is used to model the interaction between the two services. We conclude that the monopoly social welfare (SW) is closer to the SW of the social optimum than the duopoly SW. In addition, the DN scenario to offer the services through NS is more suitable than the SN scenario since the point of view of service prices, user utilities, and operator benefit. [ABSTRACT FROM AUTHOR]

The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions. [ABSTRACT FROM AUTHOR]

A compact low-profile multi-band millimeter-wave (mm-wave) reflectarray metasurface design is presented for coverage enhancement in 5G and beyond cellular communication. The proposed single-layer metasurface exhibits a stable reflection response under oblique incidence angles of up to 60 ∘ at 24 and 38 GHz, and transmission response at 30 GHz, effectively covering the desired 5G mm-wave frequency bands. The proposed reflectarray metasurface is polarization insensitive and performs equally well under TE and TM polarized incident waves due to the symmetric pattern. In addition, the low profile of the proposed metasurface makes it appropriate for conformal applications. In comparison to the state-of-the-art, the proposed reflectarray metasurface unit cell design is not only compact (3.3 × 3.3 mm 2 ) but also offers two reflections and one transmission band based on a single-layer structure. It is easy to reconfigure the proposed metasurface unit cell for any other frequency band by adjusting a few design parameters. To validate the concept of coverage enhancement, a 32 × x32 unit-cell prototype of the proposed reflectarray metasurface is fabricated and measured under different scenarios. The experimental results demonstrate that a promising signal enhancement of 20–25 dB is obtained over the entire 5G mm-wave n258, n259, and n260 frequency bands. The proposed reflectarray metasurface has a high potential for application in mm-wave 5G networks to improve coverage in dead zones or to overcome obstacles that prevent direct communication linkages. [ABSTRACT FROM AUTHOR]

Going to a stadium to see a match or a race is a thrilling experience since these magnificent structures provide an atmosphere where we can truly immerse ourselves in the competition. In today's world, stadiums play an important role in social gatherings and entertainment areas, which are capable of comfortably sheltering anywhere from 10,000 to more than 100,000 people. While the smart stadium is also sometimes called the "connected" arena with smart navigation, real-time data, better protection for athletes and so on. Smart stadium is the future of sports entertainment with the growing technology of 5G and edge computing (EC). Along with the advancements of 5G and EC, the introduction of Internet of Things (IoT) in sports will promote the use of IoT sensors for enabling preventive maintenance in stadium. Sensors deployed in the stadium can monitor the athlete's health state. Mobile EC (MEC) deploys computing resources at the edge of the network to provide computing tasks for sensors, which effectively improves the network environment and reducing transmission latency. At first, a combined power consumption, bandwidth and computing resource allocation optimization model is proposed. Then, given the limitations of probability mixing in optimization model, Markov inequality is introduced to transform for probability constraints. Finally, task offloading and resource allocation algorithm based on Lyapunov by using 5G network slicing is proposed. The simulation results demonstrate that the proposed algorithms outperform four benchmarks in terms of time-power average return, average end-to-end latency and task processing latency. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) cellular network roll-out provides high-speed performance, better coverage, and ubiquitous connectivity for the next-generation of intelligent communication systems. Compared to earlier versions, the new 5G wireless standard operates across a wider range of frequencies, which has raised aviation industry's concerns regarding safety and compatibility. For example, 5G systems operating with frequencies that are adjacent those used by radio altimeters could disrupt flight operations and navigation functions. This paper provides an overview of current research efforts assessing the 5G interference and its potential operational impact on altimeters. The work discusses the current stance of regulators and telecommunications operators worldwide on potential 5G interference with altimeters. The paper also compares the ongoing public consultations with key stakeholders globally regarding cellular systems' interference with altimeters. This work offers technical and policy recommendations to spectrum regulators and aviation authorities to inform the safe and efficient deployment of 5G spectra. This work identifies long-term solutions for achieving maximum 5G bands usability and ensuring compatibility among cellular technologies and aviation systems. • Aviation altimeters are highly susceptible to interference due to 5G mid-band. • Using directional 5G beams could be an interference mitigation solution. • Lack of definitive real-time data remains a barrier for interference estimation. • Regulations should be revised to reflect recent operational altimeter requirements. • Manufacturers need compliance with the altimeter's minimum operational standards. [ABSTRACT FROM AUTHOR]

In this article, a low-profile, high-gain meta-surface artificial intelligence process-based broadband microstrip patch antenna for 5G wireless communications is presented. The FR4 epoxy substrate material, with a dielectric constant of 4.4 and a thickness of 1.6, is used for the antenna to operate at a 20 GHz resonating frequency. The proposed antenna is simulated using the HFSS to design a simple antenna with a low profile and proper operational characteristics. Moreover, a new type of meta surface antenna with a modified patch is elongated on the surface of the antenna. The simulation of the proposed antenna highlights that the studied antenna has a maximum reflection coefficient of − 34 dB, and a bandwidth of 17–23 GHz. The proposed results, with a low profile and antenna size of 1.33λ0 × 1.33λ0 × 0.106λ0, were measured and fabricated. The meta surface appeared in the form of a mesh type of structure, fed by a microstrip patch antenna with coaxial feed cells, revealing a good arrangement with the simulated one. Moreover, the meta surface with artificial technology has empowered the arrival of new ideas and explanations in the strategy of antennas for the control of electromagnetic waves. The measured results show that the proposed antenna has the perfect axial ratio, along with a 10 dB impedance bandwidth achieved with a valued stable gain of 9–10 dBi. [ABSTRACT FROM AUTHOR]

The fifth-generation (5G) technology standard in telecommunications is expected to support ultra-reliable low latency communication to enable real-time applications such as industrial automation and control. 5G configured grant (CG) scheduling features a pre-allocated periodicity-based scheduling approach, which reduces control signaling time and guarantees service quality. Although this enables 5G to support hard real-time periodic traffics, synthesizing the schedule efficiently and achieving high resource efficiency, while serving multiple communications, are still an open problem. In this work, we study the trade-off between scheduling flexibility and control overhead when performing CG scheduling. To address the CG scheduling problem, we first formulate it using satisfiability modulo theories (SMT) so that an SMT solver can be used to generate optimal solutions. To enhance scalability, we propose two heuristic approaches. The first one as the baseline, Co1, follows the basic idea of the 5G CG scheduling scheme that minimizes the control overhead. The second one, CoU, enables increased scheduling flexibility while considering the involved control overhead. The effectiveness and scalability of the proposed techniques and the superiority of CoU compared to Co1 have been evaluated using a large number of generated benchmarks as well as a realistic case study for industrial automation. [ABSTRACT FROM AUTHOR]

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Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)