Performance Evaluation of mmWave and Sub-TeraHertz Communication Propagation Path Loss Model Simulation Using NYUSIM

The world is going through a fundamental transformation with the emergence of the intelligent information era. The key domains linked with human life such as healthcare, transport, entertainment, and smart cities are expected to elevate the quality of service with high-end user experience. Therefore, the telecommunication infrastructure has to meet unprecedented service level requirements such as ultra high data rates and traffic volume for the prominent future applications such as Virtual Reality (VR), holographic communications, and massive Machine Type Communications (mMTC). There are significant challenges identifiable in the communication context to match the envisaged demand surge. The blockchain and distributed ledger technology is one of the most disruptive technology enablers to address most of the current limitations and facilitate the functional standards of 6G. In this work, we explore the role of blockchain to address formidable challenges in 6G, future application opportunities and potential research directions.

Based on the double-flow model, a three-dimensional mathematical model of multiphase flow in RH system has been developed to predict the flow field and gas holdup distribution. Also, the circulation flow rate was measured with the water model. The results show that the nozzle blockage layers have small influence on circulation flow rate, while the effect of the blockage modalities and numbers is significant. Under the interaction of blockage modalities and numbers, the gas holdup distribution is the key factor to determine the circulation flow rate. Symmetrical blockage is an acceptable modality under the condition of a small amount of blockage, but the effect of non-symmetrical blockage on circulation flow rate is more obvious. If the blockage number is more than 3, the up-snorkel must be promptly treated or replaced.

The Multi-Point Relay (MPR) of the Optimized Link State Routing protocol reduces the flooding overhead compared with classic flooding. To select MPR nodes, HELLO messages are used. In dense population environments, the overhead of HELLO messages is critical because the HELLO messages carry all adjacent node IDs in the classical manner. Consequently, wireless bandwidth is consumed for data communications. One solution for this problem is to compress HELLO messages using a differential technique. However, few, if any, studies have applied a differential technique to HELLO messages. We introduce the novel Differential HELLO technique to reduce the overhead of the HELLO messages. The Differential HELLO technique consists of two kinds of compression methods: Chronological Compression and Topological Compression. In addition, the inconsistency problems of the 1-hop node information in adjacent nodes caused by packet loss are discussed. As solutions to the inconsistency problems, No Compression Acknowledgement (NC-ACK) and HELLO Information Forecast (HIF) have been examined. Our simulation has taken the efficiency of the Differential HELLO technique into consideration. The HELLO message overhead was reduced to 29.1 IDs from 75.8 IDs using the Differential HELLO technique at a packet loss rate of 10 -4 under random node arrangement. This result reveals that the Differential HELLO technique reduces the classic HELLO overhead by 38%. In environments with lower packet-loss rates, the Differential HELLO technique promises to offer even better performance.

Implementation of 5G network is a mammoth event in the history of wireless communication. Nonetheless, with the industry, smart cities, IoT ecosystems expanding it can no longer be considered possible to run the network in a traditional way which is naturally fixed. Network slicing is a critical technology that may empower operators to outsource several virtual as well as separate logical networks utilizing shared infrastructure. The Artificial Intelligence (AI) goes a notch higher to dynamically, proactively, and resource-effectively optimize slices to address the needs of various service-level services including ultra-reliable low-latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). In the following next-generation 5G network, AI-based network slicing is reviewed in this paper. It discusses the potential benefits of using machine learning, deep reinforcement learning, and federated learning to automate slice lifecycle management, predict traffic patterns, and allocate resources in a more efficient way. Recent reports and case studies have shown that optimization of AI-based systems can lower the latency, improve the throughput, and also decrease the energy consumption compared to the rule-based systems. Other challenges witnessed during the research are data privacy, understanding of AI designs and complexity when integrating with the old system. In addition, it focuses on standardization and regulatory plans required to implement the scaling implementation. It will be crucial in 6G networks in future to achieve intelligent slicing with diverse environments, satellite-ground relationship and immersive communications like AR/VR, holographic communications and robotics. AI-optimized network slicing will be developed to form the basis of next-generation wireless networks, balancing network virtualization and AI intelligence to enable network slices with resilience, scalability, and flexibility to accommodate next-generation digital ecosystems.

Recently, the fifth-generation (5G) of wireless network has been developed to support enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) and ultra-reliable and low-latency communications (uRLLC). However, with the tremendous increase of data services, especially driven by emerging applications such as holographic communications, augmented reality, virtual reality tactile reality, mixed reality, etc., 5G is far from enough to support the faster, more reliable and larger scale communication requirements of these services. In response, the investigation of future generation communication networks (B5G and 6G) has been triggered, which promises more powerful capacities of transmission, security, reliability and intelligence than 5G does.

The articles in this special section focus on artificial intelligence-driven fog radio access networks. To satisfy the explosively increasing demands of highspeed data applications and access requirements from a massive number of Internet-of-Things (IoT) devices, a paradigm of fog computing-based radio access network (F-RAN) has emerged as a promising evolution path for the fifth generation (5G) radio access networks. By taking full advantage of distributed caching and centralized processing, F-RANs provide great flexibility to satisfy the quality-of-service requirements of various 5G services. With the rapid deployment of 5G communication networks, the application of F-RANs to the envisioned sixth-generation (6G) mobile network has attracted extensive attention from academia, industry, and government agencies. The 6G network progress in enhanced mobile broadband, massive machine-type communications and ultra-reliable and low-latency communications will lead to the fast development of new applications, including augmented reality (AR), virtual reality (VR), holographic communications, vehicle-to-everything (V2X), self-driving cars, massive sensors connective on the ground and several tens of thousands of satellites connective in the sky.

Recently, the fifth-generation (5G) of wireless network is developed to support enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) and ultra-reliable and low-latency communications (uRLLC) (Zhang etal. (IEEE Veh Technol Mag 14:28–41, 2019)), according to the report of International Telecommunication Union (ITU). Benefitting from such high performance, 5G has opened new doors of opportunity towards emerging applications, e.g., augmented reality (AR), virtual reality (VR), tactile reality, mixed reality, etc. However, the new media, such as holographic communications, will request much higher transmission speeds up to Tera bits per second (Tbit/s) than AR and VR. Then 5G is far from enough to support the faster, more reliable and larger scale communication requirements of these services. In response, the investigation of future generation wireless networks (6G) has been triggered, which promises more powerful capacities in terms of ultra-broadband, supper massive access, ultra-reliability and low-latency than 5G does, as listed in Table 1.1 (Zhang etal. (IEEE Veh Technol Mag 14:28–41, 2019)). Table 1.1 Comparison of key performance indexes between 4G, 5G and 6GFull size table Keywords6GHeterogeneous NetworksArchitectureResource AllocationArtificial Intelligence (AI)Game Theory

In urban environments, GNSS positioning is challenging due to signal blockage and multipath effects of surrounding buildings. This study evaluates the compatibility of CORS-VRS, PPK and static GNSS methods with total station measurements to investigate their accuracy in urban conditions. For this purpose, measurements were conducted in Esenler, Istanbul on 30 September 2020. Three measurement points (P1, P2 and P3) with varying levels of obstruction were selected. The results demonstrate that static GNSS measurements (with horizontal and vertical components below 5 mm and 11 mm, respectively) are the method with the highest positional accuracy. Conversely, PPK measurements exhibited larger deviations (0.857 m (X), 0.356 m (Y), and 0.780 m (Z) in P1, 0.302 m (X), 0.215 m (Y), and 0.255 m (Z) in P1, and 0.516 m (X), 0.284 m (Y), and 0.374 m (Z) in P3. Conversely, CORS-VRS measurements exhibited deviations ranging from 13 cm to 34 cm at baseline distances when compared to total station results. The findings demonstrate that while CORS-VRS and PPK can achieve sub-decimeter accuracy, they are significantly affected by multipath and signal blockages in dense urban environments. Thus, GNSS-based positioning in urban settings should be supplemented with total station surveys when high precision (1-2 cm) is required.

Accurate estimation of path loss is essential for evaluating the impact of the propagation medium, determining transmission power requirements, and optimizing cell layouts for effective 5G millimetre wave coverage. At 28 GHz, rain attenuation is a critical factor, with its impact varying significantly based on environmental and regional characteristics. This study quantifies the degradation of 5G millimetre wave link budgets due to rainfall in South Africa and assesses the maximum coverage ranges for urban micro and urban macro deployments under varying rain intensities. The analysis focuses on Pretoria, a city characterized by diverse urban landscapes and seasonal thunderstorms. Urban micro cells are deployed on streetlights and building facades in dense zones such as Hatfield and Sunnyside to deliver high-capacity coverage. In contrast, urban macro cells target broader coverage from elevated structures, such as those in the Pretoria CBD. Using the Close-In path loss model for both line-of-sight and non-line-of-sight conditions, this study examines the relationships between link budget parameters, maximum path loss, and 5G millimetre wave link distances under rain-affected and clear-sky scenarios. The results highlight the significant influence of rainfall, particularly in non-line-of-sight conditions, and provide insights for designing efficient 5G networks tailored to South Africa’s unique climate.

5G and beyond networks have been the main focus of wireless communication society nowadays. One candidate of these networks is the usage of sub-terahertz (sub-THz) band. However, it suffers badly due to blockage whether it causes by objects or human bodies. Reflecting intelligent surfaces (RISs) is used to eliminate the effect of blockage by implementing it as an assistant to sub-THz access points (APs). In which, RISs can provide alternative line of sight (LOS) links between transmitter (TX) and receiver (RX), when the main TX-RX link is blocked. By optimal placement of RISs, they succussed in solving blockage due to static objects. But, human bodies blockage, which cannot be known and is difficult to be predicted, is still under question to model its effect on the system. In this paper, the effect of human blockage is studied under realistic scenarios in 150 THz band, where the link blockage is assumed to occur for both the direct (LOS) TX-RX link and the alternative TX-RIS-RX links. Furthermore, a trustable human blockage model, Geometrical Empirical model, is considered to describe human obstacles. In addition, we present the effect of RX height on the blockage occurrence. In our simulation results, we study the impact of blockage on the performance of RIS aided sub-THz communication system in terms of the spectral efficiency and outage probability.

In recent years, the use of unmanned aerial vehicles (UAVs) as flying base stations (BSs) has attracted widespread attention in both academia and industry. Most of the existing research on UAV networks in dense urban environment focus on omnidirectional antenna patterns, which results in severe interference and overlapping between coverage area due to dominant line‐of‐sight (LOS) links. This paper proposed a directional antennas model with tunable beamwidth and blockage effects in urban UAV networks, and derive the coverage probability of UAV networks in dense urban environment by stochastic geometry tools, where UAVs and users are deployed according to independent Poisson point process (PPP). Specifically, a realistic and mathematically tractable directional antenna pattern is adopted and radiation gain is modelled by a continuous function of the elevation angle. In addition, the blockage effects of the buildings are considered by establishing a three‐dimensional blockage model where buildings are distributed according to PPP with heights followed by Rayleigh distribution. Numerical results match well with simulations and provide optimal deployment parameters for UAV deployments.

Many biomedical sensors combine micro fluidic, electronic capacitive, and/or photonic capabilities. Micro fluidic sensors involve sealed channels through which the sample fluid containing biomedical materials flows with capacitive or photonic sensors detecting parameters contained in the liquid. However micro fluidic devices are prone to faults occurring when foreign particles in the bioliquid, or fluid bubbles, get lodged in the paths blocking a channel, thereby changing the fluidic flow in the device and affecting the parameters to be sensed. Thus, these systems require defect tolerant design in the micro fluidic and knowledge of how these changes will affect the parameters being sensed. To achieve fault tolerance we investigate a Cathedral Chamber design, with pillars supporting the roof at regular intervals. This prevents single blockages from stopping fluid flow through the system in a channel, as there are many paths. We discuss the potential causes and effects of such blockages. Monte Carlo analysis and simulations based on both randomly placed blockages and blockages occurring in low flow areas show that the Cathedral Chamber design significantly increases lifetime of the system, an average of 6 times more particles are required before full blockage occurs compared to an array of parallel channels. Fluid flow modeling shows parallel channels show rapid rise of pressure with the number of blockages while the Cathedral chamber shows much slower rise, which reaches a plateau pressure until it is blocked. The impact of these defects on the sensed parameters, such as capacitive measurement of the fluid or photonic measurements, is discussed.

Biomedical sensors combining microfluidic and electronics capabilities require defect avoidance in both the electronic processing circuits and microfluidic areas. Microfluidic sensors involve sealed channels through which sample fluids containing biomedical materials flow. Inserting microchannels between capacitive plates enable the detection of biomaterials by the changes in capacitance. However, faults occur when foreign particles, or fluid bubbles get lodged in the paths blocking a channel, thereby affecting the measured C. To achieve fault tolerance we investigate a Cathedral Chamber design, with pillars supporting the roof at regular intervals. This prevents single blockages from stopping fluid flow through the system in a channel, as there are many paths. We discuss the potential causes and effects of such blockages. Monte Carlo simulations show that the Cathedral Chamber design significantly increases lifetime of the system, an average of 6 times more particles are required before full blockage occurs compared to an array of parallel channels. Fluid flow modeling shows parallel channels show rapid rise of pressure with the number of blockages while the Cathedral chamber shows much slower rise, which reaches a plateau pressure until it is blocked. The impact of defects on the capacitive measurement is also discussed. Finally, an interesting application, one that uses patches of single chain Fragment variables (scFv's), the active part of antibodies, is also discussed.

Atmospheric turbulence and pointing errors represent substantial hurdles to free-space optical communications (FSOs), impeding their practical design. The reconfigurable intelligent surface (RIS) is an emerging technology that enables reflective radio transmission conditions for next-generation 5G/6G wireless frameworks by intelligently adjusting the beam in the desired direction using low-cost inactive reflecting elements. In this paper, we proposed an RIS-assisted FSO system for mitigating the effects of atmospheric turbulence, pointing errors, and communication system signal blockage. The probability density function and cumulative distribution functions of an FSO system composed of N-RIS elements are evaluated in a free-space environment that contains obstructions. We derived closed-form expressions for the proposed system's bit error rate (BER), outage probability, and channel capacity. The proposed system's performance is analyzed in terms of BER, outage probability, and channel capacity under various weather conditions, pointing errors, and signal blockage. The results are plotted as a function of number of RIS elements and average signal-to-noise ratio. The proposed system will be beneficial in smart-city applications since it will provide reliable connectivity in urban environments with a high population density and high-rise buildings.

Millimeter-wave (mmWave) communication has re-cently attracted substantial interest owing to its abundant bandwidth availability and low-latency capability that facilitates meeting the requirements of vehicle-to-everything (V2X) services. However, performance degradation due to signal blockage has been raised as one of the critical technical challenges. This paper investigates the signal blockage effect of a road bridge in mmWave vehicular communication by performing a ray-tracing simulation for highway scenarios. The main purpose of this study is to help the researchers understand the signal blockage effect and present considerations for cell planning of mm Wave vehicular communications in the presence of a road bridge.