5G Telecommunication Networks Research Articles

Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers

With the widespread adoption of 5G telecommunication networks, to reduce construction costs, it has become necessary to add new equipment or antennas to existing 4G and 3G telecommunication towers. This significantly changes the original aerodynamic shape of the towers, leading to a substantial increase in the wind load, which may exceed the original structure’s bearing capacity and pose a threat to the structure’s safety. This study employed three-dimensional numerical simulation methods to systematically investigate the impact of various antenna arrangement parameters, such as the arrangement number, arrangement form, and arrangement layers, on the wind load characteristics of telecommunication towers. The findings revealed that the antenna arrangement form significantly affects the sensitivity of the telecommunication tower’s wind load to the wind direction, with more uniform antenna arrangements resulting in less sensitivity. Compared to the drag coefficient and the windward base overturning moment coefficient, the tower’s lateral force coefficient and the crosswind base overturning moment coefficient are more sensitive to changes in the wind direction. The change patterns in the tower’s overturning force coefficient and overturning moment coefficient with the antenna arrangement number are essentially the same. However, as the antenna arrangement number increases, the growth rate of the tower’s overturning moment coefficient is about twice that of the overturning force coefficient. The tower’s overturning force coefficient increases approximately linearly with the increase in antenna arrangement layers, while the tower’s overturning moment coefficient exhibits a nonlinear increase with the increase in antenna arrangement layers. The rate of increase in the wind load with the antenna arrangement layers is significantly greater than that with the antenna arrangement number. Thus, to reduce wind load, it is advisable in practical engineering applications to increase the antenna arrangement number per layer, thereby reducing the antenna arrangement layers. The study also summarized a calculation method for the structural wind load of telecommunication towers, taking into account the influence of antenna arrangement parameters, providing a reliable basis for the structural design and safety assessment of telecommunication towers in practical engineering.

Artificial Intelligence Driven 5G and Beyond Networks

5G networks and beyond are expected to meet numerous service requirements in various aspects of our daily lives. At the same time, the functional complexity of 5G telecommunication networks increases by an order of magnitude compared to existing networks. 5G data rates are dramatically faster, connection density is higher, and latency is much lower, among other improvements. An efficient 5G network cannot be complete without incorporating artificial intelligence (AI) techniques. All this requires the use of new technologies, including artificial intelligence, to ensure the stable operation of telecommunication networks, methodology, system analysis, and key results. Scientific tasks for 5G communication networks are identified where the use of artificial intelligence, including machine and deep learning, seems appropriate. Practical Relevance. The results of the work may be useful in training in networks and telecommunication systems and in defining new scientific tasks for PhD students.

A Novel Reverberation Chamber for In Vitro Bioelectromagnetic Experiments at 3.5 GHz

In this article, a mode-stirred reverberation chamber (RC) was designed and proposed for the first time as a cell culture incubator for in vitro electromagnetic waves exposure of adherent cells in tissue culture plates (TCPs). Typical cell incubators require specific conditions, such as temperature of 37 °C and humidity rate of 95%, which are challenging conditions for an RC. The chamber was characterized as an RC through an innovative experimental methodology based on the measurements of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> parameter of the emitting antenna. The proposed RC is adapted for in vitro bioelectromagnetic experiments for simultaneous exposure of up to 10 TCPs under highly homogeneous exposure conditions at 3.5 GHz, i.e., the mid-frequency band of the 5G telecommunication networks. Experimental results showed that the specific absorption rate (SAR) in the exposed samples extracted from temperature measurements was similar (an acceptable maximum variation lower than 30% was observed) in reason of the homogeneity and the uniformity of the field within the chamber. Specifically, measured SAR values were around 1.5 and 1 W/kg per 1 W incident, in 6-well or 96-well plates used for biological exposure, respectively. To validate our system, numerical simulations were performed. Overall, we showed that experimental and numerical SARs are in good agreement with differences <30% considering the standard deviation.

Design of deep learning model for radio resource allocation in 5G for massive iot device

With recent advancements in Internet of Things (IoT) communications, the demand for fastest communication is an utmost concern of the IoT technology. The advent of 5G telecommunication networks enables to bridge the demand on satisfying the Quality-of-Service (QoS) concerns in IoT communication. The massive number of devices in IoT communication is henceforth do not lie under limited resource allocation by embedding the 5G telecommunication network. The existing deep learning approaches lack in the allocation of resource in the energy constrained environment. In this paper, we address the above limitation of allocation the resource to prominent IoT devices using Deep Belief Network. It is efficient in the utilization of hidden layers and the probabilistic correlation among the instances are constructed effectively. In this Deep Belief Network, the adoption of rules will imply the resource allocation with the devices of top priority and it reduces based on the priority. DBN learns the context of the 5G and connected IoT devices whereas the resources are provisioned effectively through the learning. The proposed strategy beats the current state-of-the-art techniques, whereas the DBN achieves 74 % of successful job completion that is effective compared to other existing strategies. The simulation is performed to test the efficacy of Deep Learning on allocation 5G resources to IoT model. The results show that the proposed model achieves higher level of allocating the resources than other methods.

Improved Radio Resource Allocation in 5G Network Using Fuzzy Logic Systems

With recent advancements in machine-to-machine (M2M), the demand for fastest communication is an utmost concern of the M2M technology. The advent of 5G telecommunication networks enables to bridge the demand on satisfying the Quality-of-Service (QoS) concerns in M2M communication. The massive number of devices in M2M communication is henceforth do not lie under limited resource allocation by embedding the 5G telecommunication network. In this paper, we address the above limitation of allocation the resource to prominent M2M devices using Adaptive Neuro Fuzzy Inference System (ANFIS). In ANFIS, the adoption of rules will imply the resource allocation with the devices of top priority and it reduces based on the priority. The ANFIS controller acts as a central controller that implies the resource allocation with its rules on the M2M devices. The simulation is performed to test the efficacy of fuzzy logic system on allocation 5G resources to M2M model. The results show that the ANFIS model achieves higher level of allocating the resources than other existing methods in terms of reduced network delay, increased throughput, packet delivery rate and energy efficiency.

Homeschooling using Technology Enhanced Learning as an adapting learning strategy during COVID-19 Outbreak

With the outbreak of COVID-19 in 2020, the start of an exciting era in medicine and science, the development and maturation of several digital technologies that can be applied to tackle major clinical problems and diseases is mandatory. These digital technologies include the internet of things (IoT) with next-generation 5G telecommunication networks, big-data analytics; artificial intelligence (AI) that uses deep learning; and blockchain technology .

Probabilistic Attenuation Nowcasting for the 5G Telecommunication Networks

In this letter, we propose a novel approach to produce attenuation forecasts for microwave links using a probabilistic approach. It uses ensembles of forecast rainfall fields to easily derive attenuation forecasts for specific frequencies. The proposed approach uses the short-term ensemble prediction system (STEPS) to generate ensembles of high, spatial and temporal, resolution forecast rainfall fields based on observed weather radar fields with lead times of 15–90 min. Attenuation forecasts could eventually be used by telecommunication operators to drive the operation of wireless networks and ensure their maintenance during severe and extreme rainfall events. This study used 109 microwave links ranging from 15 to 40 GHz to verify the results of this probabilistic attenuation forecast. Results suggest that the STEPS-based attenuation forecasts were within the narrow span of the 90% confidence region for all microwave links tested up to 30 min lead time, decreasing for longer lead times. Examples of how the proposed approach can be used to derive a detailed probabilistic attenuation forecast for multiple lead times within a domain of few kilometers, as well as probability of attenuation maps for large areas are shown.

Design of compact, high-speed and low-loss silicon-on-silica electro-optic modulators

Throughout a careful step-by-step study, two simple designs of electro-optic modulators are proposed. The study shows the effect of dimensions and doping concentration on the performance parameters such as the modulation bandwidth, the size, the insertion loss and the extinction ratio. One design shows a modulation bandwidth of with a relatively short phase shifter length of , a low optical insertion loss of and a very high extinction ratio of . The other one shows a bandwidth of , a phase shifter length of , an optical insertion loss of and an extinction ratio of . It is shown that these two designs can fit to the requirements of the 5G telecommunications networks at different points which require different speeds of operation. The designs feature the complementary-metal-oxide-semiconductor technology advantages of ease and low-cost of fabrication.

Implementation, Characteristics, and Effectiveness of an Ophthalmic Hospital-Based Virtual Clinical Service in China During COVID-19

Background: The COVID-19 pandemic crisis is posing challenges for clinical practice worldwide. We describe the characteristics and effectiveness of a virtual clinical service run by a tertiary ophthalmic center in China with an aim to provide practical guidance for such services during and beyond the pandemic. Methods: We conducted a longitudinal observational study. To provide the diagnosis and treatment of eye diseases under stringent epidemic control measures, the Zhongshan Ophthalmic Center (ZOC) established a virtual clinical service (virtual 2020) by harnessing several digital technologies (5G telecommunication networks, big data analytics, artificial intelligence (AI) and blockchain technology). Multiple interrelated services were offered online, including AI prescreening, virtual live consultation, and online pharmacy. We extracted data from the online clinical service records, along with on-site face-to-face (F2F) clinical records obtained from February 1 to March 13 in 2020 (F2F 2020) as well as a similar period in 2019 (F2F 2019) for analysis. We analyzed the clinical service pattern by day and time; indication of visit and demographics of age, gender, and geographical origin between three groups: virtual 2020, F2F 2020, and F2F 2019. Findings: A total of 38,038 visits to the ZOC were conducted online and F2F from February 1 to March 13, 2020, including 10,641 visits from an AI chatbot, 9,850 virtual live consultations by 127 doctors, and 17,547 on-site F2F consultations in the clinics. With the gradual opening of on-site outpatient and emergency services, online service numbers steadily increased. The AI chatbot services after office hours (8 pm to 8 am) accounted for 26.9% of the total visits, which was significantly higher than the proportions of virtual live consultations (10.9%) and on-site F2F consultations (3.5%) in 2020. Among the indications for virtual live consultation, specific disease consultation was the most common across all ages (64.7–70.7%); younger patients tended to have visual symptoms (18–34 years old, 60.4%), whereas seniors were more likely to require prescription renewal (>55 years old, 63.5%). Virtual live consultation in 2020 was more common in younger (median age 32 years) and female patients (53.3%) than in the F2F 2020 or F2F 2019 groups. Ocular surface diseases were the most frequent diagnosis in the virtual live consultations, which differed from the top diagnosis in F2F 2020 (retinopathy) and F2F 2019 (refraction) groups (P<0.05 comparisons between groups). Interpretation: The management of many ophthalmic diseases online in a virtual hospital setting can be implemented and is complementary to those of physical on-site F2F clinics. Virtual clinical service may be a useful model of care in the post-COVID19 pandemic “new normal”. Funding Statement: The study was supported by the National Key RD Guangzhou Key Laboratory Project (202002010006); Guangdong Science and Technology Innovation Leading Talents (2017TX04R031); the National Natural Science Foundation of China-General Programs (81770967, 81873675); National Natural Science Fund for Distinguished Young Scholars (81822010); the National Natural Science Foundation -Young Scientists Fund (81800810) and the Science and Technology Planning Projects of Guangdong Province (2018B010109008). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study followed the principles outlined in the Declaration of Helsinki. The study protocol was approved by the ethical board committee of the Zhongshan Ophthalmic Center, Sun Yat-sen University (2020KYPJ012).

Fiber-Based UTC Dissemination Supporting 5G Telecommunications Networks

Any mobile telecommunications network requires syntonization among its various elements. The need to exploit the available radio spectrum efficiently and providing new kinds of services render frequency syntonization insufficient. Phase and time-of-day synchronization will be necessary in the future. Thus, network operators are searching for efficient and reliable synchronization architectures. In this article, an example of such an architecture, applicable to fifth generation mobile networks, is presented, based on the requirements published in the latest ITU-T Recommendations. For supervision of the performance of the synchronization network, the technology of optical time transfer (OTT) is proposed, which allows dissemination of an accurate timescale such as a UTC realization to selected nodes of a coherent network primary reference time clock. The OTT realized so far and its current and future role in the network of Deutsche Telekom are discussed, and representative measurement results are shown.

A compact 120 GHz monolithic silicon-on-silica electro-optic modulator

A novel electro-optic modulator using the silicon-on-silica platform is proposed. The modulator utilizes a modified version of the gate-all-around switching mechanism which is well-known in MOSFET transistors. The waveguide silicon core is surrounded by oxide and metal to increase the effect of the applied voltage in charge depletion and accumulation and hence the optical phase shift. The modulator features a very high switching speed of $$120 \;{\text{GHz}}$$, thanks to its very low capacitance, with a total insertion loss of $$4.6 \;{\text{dB}}$$ and a phase-shifter length of $$500 \;\upmu{\text{m}}$$. The proposed modulator can therefore serve in high speed applications such as the backbone circuits of the new 5G telecommunications networks.

The State and Science in the Trump Era: Preliminary Results

The global trends of recent decades show new challenges to the position of the United States as a leader in the field of science and innovation. The response measures taken by the Trump administration and Congress are aimed at the further development of the U.S. science and technology capabilities with a focus on modern "breakthrough" technologies (artificial intelligence, quantum information science, biotechnology, 5G telecommunications networks, space exploration) as well as on expanding public-private partnership. While the White House continues to insist on cutting federal spending on nondefense R&D to spur defense developments, Congress is making decisions based primarily on research agencies’ budget requests, taking into account new initiatives and program changes.

Cybersecurity, National Security and Trade in the Digital Era

The digital transformation, and especially the implementation of the Internet of Things with the advent of 5G telecommunications networks, is creating national security concerns that threaten to disrupt international commerce across geopolitical divides, including a decoupling of US- and China-centred cyberspheres. This note considers the nature of the cybersecurity concerns that have been raised in the decoupling debate and the changing context for national security. It concludes that we do not yet have a good idea of what we need to do, and we do not who will be doing it. This means that it is premature to attempt to craft a national security regime for the emerging data-driven economy. Data is not treaty ready, and the world, unfortunately, is not yet ready to deal with the regulation of the data-driven economy.

Resource Allocation for Network Slicing in 5G Telecommunication Networks: A Survey of Principles and Models

With the rapid and sustained growth of network demands, 5G telecommunication networks are expected to provide flexible, scalable, and resilient communication and network services, not only for traditional network operators, but also for vertical industries, OTT, and third parties to satisfy their different requirements. Network slicing is a promising technology to establish customized end-to-end logic networks comprising dedicated and shared resources. By leveraging SDN and NFV, network slices associated with resources can be tailored to satisfy diverse QoS and SLA. Resource allocation of network slicing plays a pivotal role in load balancing, resource utilization, and networking performance. In this article, we focus on the principles and models of resource allocation algorithms in 5G network slicing. We first introduce the basic ideas of the SDN and NFV with their roles in network slicing. The MO architecture of network slicing is also studied, which provides a fundamental framework of resource allocation algorithms. Then, resource types with corresponding isolation levels in RAN slicing and CN slicing are analyzed, respectively. Furthermore, we categorize the mathematical models of resource allocation algorithms based on their objectives and elaborate them with typical examples. Finally, open research issues are identified with potential solutions.

Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art

The exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to Music Information Retrieval (MIR) field. MIR is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social media and qualitative recommendations in music services. Moreover, 5G telecommunications networks, characterized by “near-instant and everything in the vicinity talks with one another,” with exponentially faster download and upload speeds, may change the existing models and create a new age of interconnectedness. This paper aims at showing some of the already highly exploited technologies and crowdsourcing models applied to music processing. Several studies are discussed in details, such as, e.g., deep learning applied to music, a way to generate an expanded training sets using 2-D data such spectrograms, mel-cepstrograms, chromagrams, and waveform-based representations of the signal instead of feature vectors in machine learning, allowing to retain all nuances related musical articulation in the signal. Also, a discussion is to be outlined, expanding the issue of the impact of these new technologies on the artistic and aesthetic values of music.

Fiber-Optic Time Transfer for UTC-Traceable Synchronization for Telecom Networks

A robust and reliable synchronization network, able to distribute signals traceable to a recognized standard, is crucial for the operation of future 5G telecommunication networks. In this article we present the results of time transfer using optical fibers. The main goal is to test the long-term capability of ELSTAB technology (developed by AGH) to deliver time and frequency signals traceable at the sub-nanosecond level to UTC in a real telecommunication environment. In an ongoing cooperation between Deutsche Telekom (DTAG), the Physikalisch- Technische Bundesanstalt (PTB) and AGH University of Science and Technology, we deliver UTC -- as realized by PTB in Braunschweig -- to a test center of DTAG located in Bremen. For this purpose, a fiber optic link has been operated since July 2015. The results obtained show that the operator of a telecom network may use such a stabilized fiber optic link as a reliable source for synchronization signals with a precision and accuracy superior to those obtained using a state-of-the-art GNSS time receiver. Moreover, a fiber optic link delivering UTC traceable signals increases the robustness and reliability of the network's synchronization chain by making it less dependent on GNSS.