Mobile Broadband Research Articles

Cross-country convergence of broadband Internet access

Technology diffusion contributes to the technological and economic convergence of countries. The rapid spread of Internet technologies creates bases to put forward a hypothesis about the convergence of countries in terms of their level of penetration. The purpose of the study is to identify a trend towards convergence or divergence in both fixed and mobile broadband for the countries of the world as a whole and for groups of countries identified on the basis of the following criteria: geographical (by geographic macro-regions), economic (by national income per capita), and institutional (according to membership in an international organization). The data sources were the open data of the International Telecommunication Union. The research methodology includes the construction of dynamic models on panel data to test the hypothesis of the presence of unconditional beta convergence. In addition, the absolute scale of the digital divide between groups of countries in terms of broadband Internet access was estimated using a sigma convergence model. The results of the study indicate the presence of beta convergence for both fixed and mobile broadband. This pattern is observed both for the full sample of countries and for geographic regions, with the exception of Oceania. Also, beta convergence is typical for groups of countries identified by the level of income per capita and participation in the Organization for Economic Cooperation and Development. At the same time, the results of the study indicate a persistent digital divide between countries in terms of Internet broadband penetration. The practical significance includes recommendations developed on the basis of the research findings, aimed at implementing a strategy for accelerated technological development in order to stimulate the spread of mobile broadband access and expand the telecommunications infrastructure.

Statistical Characterization and Modeling of Radio Frequency Signal Propagation in Mobile Broadband Cellular Next Generation Wireless Networks

An accurate assessment of the spatial and temporal radio frequency channel characteristics is essential for complex signal processing and cellular network optimization. Current research has employed numerous models to figure out how much signal propagation loss occurs along the propagation paths. However, there are issues in finding the right model for a particular terrain because these models are not universally applicable. By employing the lognormal function and the Maximum Likelihood model, a hybrid probabilistic statistical distribution model was evolved. Three LTE cell site locations in Port Harcourt, Nigeria, were used to create a hybrid model that describes the functional stochastic signal propagation loss in the area. The evaluated Maximum Likelihood model accurately estimates the relevant wireless channel properties based on observed field data. The minor square regression approach and the proposed hybrid parameter estimation methodology are compared. When it comes to estimating standard deviation errors as well as the root mean square errors, the ML‐based approach consistently outperforms the least square regression model. Finally, the proposed hybrid probabilistic statistical distribution model would be useful for mobile broadband network planning in related wireless propagation conditions.

Concurrent Multiband Direct RF Sampling Receivers

Direct radio frequency (RF) sampling receivers are investigated for use in concurrent multiband reception for mobile broadband (MBB) applications. The recent proliferation of different frequency bands and standards in wireless communications has allowed large increases in mobility and throughput, but the number of receivers in a device is limited by physical space and power consumption. Software Defined Radio (SDR) is increasingly being explored to reduce the number of analog RF components required. This paper examines the use of direct RF digitization, allowing tunable and concurrent reception of multiple bands with a single RF front-end. Full mathematical models of both Nyquist and subband sampling receivers are presented and used to investigate a quadband LTE receiver, which is modeled in Simulink and implemented in a hardware-in-the-loop (HWIL) testbed. Individual bands are simulated to have at worst -95dBm sensitivity for 16-QAM with Nyquist sampling and -83dBm with subband sampling. Desensitization of the receivers due to multiband processing is evaluated theoretically and experimentally, showing a maximum of 3dB degradation, which is within the LTE standard for adjacent band interference.

INFORMATION AND COMMUNICATION TECHNOLOGIES AS A VECTOR OF THE DIRECTION OF E-GENERATION OF THE COUNTRY

In the modern post-industrial society, information is gaining more and more importance and the properties of a strategic resource, becoming a decisive factor in modern political and economic development. Today, the information product is the basis of increasing the production of material goods and one of the determining factors of the democratic transformation of management. The informational role in the preparation and adoption of highly effective decisions makes high demands on its quality in the process of forming the information technology system in public administration. Over the past two decades, information and communication technologies (ICT) have contributed to a dramatic transformation of society, culture, and the economy. The world has witnessed changes brought about by the rapid advancement of technologies in the ICT ecosystem such as social media, big data and the Internet. Mobile technology and broadband access are already widespread in developed countries and are now expanding rapidly in developing and emerging markets. Social media has significantly affected the way people interact with each other and with their governments. Open government data and cloud computing combined with increased mobile consumption have further enriched economic systems. The article reveals the place and role of information and communication technologies in the conditions of transformation of state administration and the business community. The role of information and communication technologies as an authoritative and significant factor at the state level is explained. It has been confirmed theoretically and from a practical point of view that information and communication networks and systems are an independent environment in which the latest business processes and economic principles on the issues of effective state management, affecting all sections of society, are generated. For the successful implementation of projects and their management in the field of electronic government, it is very important to understand that information technologies act only as a tool for the transformation of administrative processes and structures and cannot by themselves solve the problems facing state structures.

A Study to Assess The Excess Use of Smart Phone Among Adolescents (17-18 Years) with a View to Develop Information Pamphlet on Ill Effects of Smart Phone in a Selected College of Mysuru

Adolescent has been defined by WHO as the period of lifespan of the age between 10-19 years. It is formative period of life when maximum amount of physical, psychological and behavioral changes take place. A smart phone is a handheld personal computer. It possesses extensive computing capabilities, including high-speed access to the internet using both Wi-Fi and mobile broad band service. It is a dependence syndrome seen among adolescents those who exhibit problematic behaviours. The main aim of this study was to assess the excess use of smart phone among the adolescents and to develop information pamphlet on ill effects of Smartphone among adolescents. The research approach selected for the study was descriptive survey approach and research design was descriptive design. The sample of present study comprised of adolescents (17- 18 years) in JSS Arts, commerce and science college of Mysuru. In the present study, 60 samples were selected through non probability convenience sampling technique. Data collection tool includes Personal variables proforma to collect the sample’s demographic profiles and Rating scale to assess the excess use of smart phone among adolescents (17-18 years). Findings of the study revealed that mean scores of excess use of Smartphone of adolescents was 40.7 with standard deviation of ±5.1 and the scores were ranged between 32-48. Out of 60 Samples, 49(81.7%) of adolescents are at the potential risk, and 11(18.3%) of adolescents are at high risk for excess use of Smartphone.

5G-enhanced Positioning Accuracy in Smart City

The new 5G mobile network promises to enhance existing services or include new ones to address key challenges presented by smart city stakeholders (citizens, municipalities, politics, industries, architects, etc.) to improve system implementations. These challenges cover various smart city fields such as transportation, environmental monitoring, healthcare, industrial automation, smart grid, etc. Thus, the main objective of 5G functionalities is to provide solutions to the various identified needs, which are defined as constraints and requirements. Therefore, three categories of 5G-based use cases have been defined: Enhanced Mobile Broadband (eMBB), Massive Machine Type Communications (mMTC), and Ultra-reliable and Low Latency Communications (uRLLC). Each group involves a set of use cases and characterized by specific technical features that address the corresponding needs. However, accurate and real-time positioning information is a vital requirement common to all three categories, but the degree of performance varies across scenarios and descriptions. Therefore, this work presents a summary of existing positioning technologies crossed with wireless technologies and smart city use cases to highlight the potential that will add accurate and real-time positioning to 5G capabilities. 5G promises decimeter accuracy in some critical use cases.

Performance Analysis of Support Vector Machine Learning Based Carrier Aggregation Resource scheduling in 5G Mobile Communication

The 5G cellular system will enable heterogeneous networks that incorporate 5G, 4G, Wi-Fi, and other telecommunication connectivity. This will result in huge changes in existing infrastructure and architecture network. Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and massive Machine Type Communication (mMTC) are some of the 5G's basic application cases. The variety of heterogeneous networks makes it challenging to manage, network traffic, inter-cell, and intra-cell interfaces. Due to diverse interfaces and data transmission rates, network traffic in heterogeneous networks can be difficult to manage and control. Advanced techniques including Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL) are used in the 5G Network to overcome such issues. In this paper, a Support Vector Machine (SVM) learning-based resource allocation approach for heterogeneous networks is designed. A machine learning method is proposed to enhance the performance of 5G NR mobile networks. This method is used to upgrade the throughput of the overall networks. The SVM learning function detects by splitting network data of channel state information (CSI). The considered channel state data of two variables as labels with X1 and X2 and trained using SVM-LINEAR, SVM-RBF, and SVM-SIGMOID. The proposed SVM classifier by splitting data for training 80% and testing 20%. A Static Error rate is set as a threshold limit at 10% (0.10) of BLER (Block Error Rate). If the error rate passed the threshold, then update Carrier Aggregation with aggregated component else set carrier aggregation with ordinary carrier component values to Zero. The proposed approach further compares with the round robin (RR), best channel quality indicator (BCQI), fractional frequency reuse (FFR), MU-MIMO, and beamforming resource scheduling techniques. The innovative results indicated that the proposed approach enhanced spectral efficiency, average cell throughput, edge throughput peak throughput, and fairness index.

Design and simulation of a low return loss UWB CPW-fed patch antenna for mobile wireless communications

With the recent development of wireless communication systems and the 5G spectrum, mobile broadband technology (MBB) has been thriving. In this contribution, the design of an Ultra Wide Band T-slotted rectangular microstrip patch antenna is presented which is suitable for high data rate applications. The antenna is fed using a coplanar waveguide and is designed for two central operating frequencies, the lower resonant frequency at 3.6 GHz, an internationally recognized standard for 5G wireless mobile communications and a higher frequency at 6.8 GHz, which is part of the new wifi-6E standards. All data of the characteristic parameters have been obtained by using the Computer Simulation Technology Microwave Studio Student suite 2021 (CST MWS).

QoE-Driven Optimization in 5G O-RAN-Enabled HetNets for Enhanced Video Service Quality

Many innovative applications are projected to be supported by 5G networks across three verticals: enhanced mobile broadband, ultra-reliable low-latency communication, and massive machine-type communication. Given the constraints of the current radio access networks (RANs), accommodating all these applications, considering their quality of service and quality of experience (QoE) requirements is not practical. OpenRAN is a new architecture touted as the most viable next-generation RAN solution. It promotes a software-defined component, the RAN intelligent controller (RIC), which governs and supplies intelligence to optimize radio resource allocation, implement handovers, manage interference, and balance load between cells. RIC has two parts: non-real-time (non-RT) and near-RT. This article introduces a novel QoE enhancement function (QoE <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> F) xApp to enhance the functionality of a near-RT RIC through providing efficient resource provisioning to users requesting high-resolution video services. It deploys an innovative adaptive genetic algorithm to perform optimal user association along with resource and power allocation in HetNets. Simulation results demonstrate superior QoE <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> F xApp performance in terms of VMAF and MoS for two different resolution videos and diverse numbers of users.

Machine Learning-Based Uplink Scheduling Approaches for Mixed Traffic in Cellular Systems

The problem of the uplink resource allocation of mixed-traffic types in cellular networks is a challenging problem that has not been addressed sufficiently in the literature. In this paper, we consider the 5G uplink scheduling for Ultra-Reliable and Low Latency Communications and enhanced Mobile Broad-Band (eMBB) traffic types. There are three main scheduling techniques to be considered, namely, the grant-based (GB), the semi-persistent, and the grant-free (GF) techniques. Furthermore, there are three different schemes used in GF scheduling, namely, the reactive, the k-repetitions, and the proactive schemes. We devise a mathematical model for the GF services using the k-repetitions scheme as the first model to define such traffic in a single cell. In addition, the GB scheduling model for eMBB traffic is adapted to fit our problem. We formulate the scheduling problem as a mixed-integer non-linear programming optimization problem. We introduce a complete system model that includes GF and GB subsystems. We introduce a novel mixed scheduler that combines the advantages of two well-known schedulers in the literature. We introduce novel machine-learning-based scheduling algorithms and evaluate them in comparison to well-known algorithms in the literature in addition to the optimal bound that we also derive. The results show that the proposed algorithms produce near-optimal results in real time.

The Effects of Mobile Broadband Coverage on Multidimensional Poverty in Mexico

The Effects of Mobile Broadband Coverage on Multidimensional Poverty in Mexico

Deep Reinforcement Learning Based Resource Allocation Approach for Wireless Networks Considering Network Slicing Paradigm

In this paper, we present an approach for resource scheduling in wireless networks based on the Network Slicing (NS) paradigm using Double Deep Q-Network (DDQN) Reinforcement Learning (RL) algorithm. More specifically, we propose a joint power and Scheduling Block (SB) allocation algorithm for networks with NS. The reinforcement learning algorithm applied to the resource allocation problem is formulated using state transitions regarding the system dynamics. We also present an algorithm, namely Network Slicing based on Reinforcement Learning (NSRL) that combines the proposed reinforcement learning based resource allocation with an approach based on reservation and sharing of resources among the slices where each RL agent acts in one slice. Simulations are carried out considering User Equipments (UEs) within a small cell coverage area - (Small Cells) with different Modulation and Coding Schemes (MCS) standardized by the 3rd Generation Partnership Project (3GPP) based on a simplified NS scenario with fifth generation wireless network (5G) characteristics. In the simulations, two slices are considered for the UEs: one considering Ultra-reliable and Low Latency Communications (URLLC) and other related to enhanced Mobile Broadband (eMBB) services. Simulation results show that the NSRL algorithm efficiently allocates power and SBs, outperforming other algorithms in the literature.

An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

5G use cases, for example enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and an ultra-reliable low latency communication (URLLC), need a network architecture capable of sustaining stringent latency and bandwidth requirements; thus, it should be extremely flexible and dynamic. Slicing enables service providers to develop various network slice architectures. As users travel from one coverage region to another area, the call must be routed to a slice that meets the same or different expectations. This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks. Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies. Therefore, this study discusses the network model’s design and implementation of self-optimization Fuzzy Q-learning of the decision-making algorithm for slice handover. The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service (QoS), specifically the probability of the new call to be blocked and the probability of a handoff call being dropped. Hence, within the network model, the call admission control (AC) method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity. Moreover, to mitigate high complexity, the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces. The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.

Development of a metric for assessing the competitiveness of Ukraine according to the progress of the digital transformation of the economy

Ukraine’s prioritization of entry into the European digital market as a foreign policy direction highlights the urgency of incorporating the global digital economy and society index (DESI) into the national statistical monitoring system. The article asserts that DESI introduction is a pressing issue. It was emphasized that although Ukraine has declared its integration into the EU's single digital market, the country is not currently participating in any international rating to assess the competitiveness of its digitalization progress. This is due to the absence of any strategic or conceptual documents that support the use of indices of the country's digital evolution. By not implementing new and improved tools for measuring digitalization as a factor of economic growth, Ukraine is severely limited in reflecting the use and impact of digital technologies, such as AI, data analytics, IoT, 3D print, automation and robots, Cloud, 5G mobile broadband, and blockchain, on the aggregate value added of different economic sectors. Currently, only the metric for determining the Digital Transformation Index of Ukraine's regions has been approved in Ukraine at the official level. However, this metric does not meet the requirements of Eurostat and therefore cannot be utilized for international comparison. It is imperative that the global Digital Economy and Society Index (DESI) metric is implemented in Ukraine's domestic practice. The constituent elements of DESI, which include connectivity, human capital, use of internet services, integration of digital technology, and digital public services, must be taken into consideration. Accordingly, an assessment was conducted to determine Ukraine's readiness for the implementation of DESI. It is justified that Ukraine's participation in the formation and presentation of information about the DESI index will allow not only to have an objective assessment of the country's place in global trends, but also to have extremely important information for international investors regarding Ukraine's confirmation of commitment to the principles of openness and transparency assumed by international obligations to enter the single digital market by harmonizing its statistical system with EU standards and practices.

A perspective vision of micro/nano systems and technologies as enablers of 6g, super-iot, and tactile internet [point of view

Modern research in technology fields, such as electronics, distributed networks of sensing/functional nodes, and wireless and wearable devices, is relentlessly converging around wide application paradigms, such as Internet of Things (IoT) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> and Internet of Everything (IoE) <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> — <xref ref-type="table" rid="table1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Table 1</xref> , at the end of section, offers a full list of used acronyms. From a different perspective, recent advances in electronics, hardware (HW) technologies, information technology (IT), and artificial intelligence (AI) for telecommunication networks, standards, and protocols look to unavoidably fall under the umbrella of fifth generation of mobile communications (5G) <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> . Even though they appear orthogonal to each other, IoT, IoE, and 5G are closely linked together. In a nutshell, IoT and IoE target pervasivity of services, while 5G is the pillar upon which transmission of massive amounts of data and information should lay <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> . As brief recap, 5G poses on the three cornerstone drivers of enhanced mobile broadband (eMBB), massive machine-type communications (mMTCs), and ultrareliable low latency communications (URLLC) <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> , to enable data-centric applications such as machine-to-machine (M2M), vehicle-to-vehicle (V2V), and vehicle-to-everything (V2X) communications, along with virtual reality (VR), augmented reality (AR), and extended reality (XR).

Optimizing Mixed Capacity of Extended Reality and Mobile Broadband Services in 5G-Advanced Networks

Optimizing Mixed Capacity of Extended Reality and Mobile Broadband Services in 5G-Advanced Networks

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

The outright aim of Beyond Fifth Generation (B5G) communication is to bring a revolution in Quality of Service (QoS) through enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), and massive Machine Type Communication (mMTC). Thereby, due to this massive expansion in the communication paradigm, interference is bound to surface unexpected challenges in the wireless domain. Thus, interference mitigation is a foundational aim in the research paraphernalia of B5G communication. Presently, Software Defined Networking (SDN) is emerging to empower wireless communication with centralized routing-based interference mitigation. With this premise, we aim to present a focused review on SDN-based interference mitigation in wireless communication. Initially, we discuss current research horizon in the subject domain and briefly explore literature for routing-based interference mitigation. Thereby, we analyze the potential of SDN through evaluation of existing solutions for interference mitigation in B5G communication. We conclude our survey by highlighting prominent future research directions in SDN-based interference mitigation.

Modeling Variation in Mobile Download Speed in Presence of Missing Samples

A stably fast mobile broadband connectivity is key to customer retention. Mobile networks, however, suffer unpredictability in performance. Analyzing variability in network speed is, therefore, challenging since it tends to exhibit patterns at several time scales. Additionally, frequently monitoring it over time, is costly. In this paper, we analyze speed measurements from 78 stationary probes, spread across Norway. Monitoring was performed thrice per day across the year, to assess performance of the two largest network operators. Despite being unique, the dataset involves a non-trivial extent of missing data. This study investigates the effect of missing data on the extracted performance patterns. We capture patterns with tensor factorizations, that show that missing data at random has a minimal effect on the identified patterns, and that depending upon the determinism of an operator's performance, the acceptable size and structure of missing data varies. Our analysis shows that, for a probe, the difference in speed variation between real and imputed speed values can be around 7% for up to 40% missing data. We also identify that congestion, routine maintenance and sub-optimal network configuration cause high speed variability. These findings can help operators improving their offerings and deciding on optimal performance monitoring frequency.

On the Coexistence of eMBB and URLLC in Multi-Cell Massive MIMO

The non-orthogonal coexistence between the enhanced mobile broadband (eMBB) and the ultra-reliable low-latency communication (URLLC) in the downlink of a multi-cell massive MIMO system is rigorously analyzed in this work. We provide a unified information-theoretic framework blending an infinite-blocklength analysis of the eMBB spectral efficiency (SE) in the ergodic regime with a finite-blocklength analysis of the URLLC error probability relying on the use of mismatched decoding, and of the so-called saddlepoint approximation. Puncturing (PUNC) and superposition coding (SPC) are considered as alternative downlink coexistence strategies to deal with the inter-service interference, under the assumption of only statistical channel state information (CSI) knowledge at the users. eMBB and URLLC performances are then evaluated over different precoding techniques and power control schemes, by accounting for imperfect CSI knowledge at the base stations, pilot-based estimation overhead, pilot contamination, spatially correlated channels, the structure of the radio frame, and the characteristics of the URLLC activation pattern. Simulation results reveal that SPC is, in many operating regimes, superior to PUNC in providing higher SE for the eMBB yet achieving the target reliability for the URLLC with high probability. Moreover, PUNC might cause eMBB service outage in presence of high URLLC traffic loads. However, PUNC turns to be necessary to preserve the URLLC performance in scenarios where the multi-user interference cannot be satisfactorily alleviated.

Coexistence of URLLC and eMBB Services in MIMO-NOMA Systems

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are two major expected services in the fifth-generation mobile communication systems (5G). Specifically, eMBB applications support extremely high data rate communications, while URLLC services aim to provide stringent latency with high reliability communications. Due to their differentiated quality-of-service (QoS) requirements, the spectrum sharing between URLLC and eMBB services becomes a challenging scheduling issue. In this paper, we aim to investigate the URLLC and eMBB co-scheduling/coexistence problem under a puncturing technique in multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. The objective function is formulated to maximize the data rate of eMBB users while satisfying the latency requirements of URLLC users through joint user selection and power allocation scheduling. To solve this problem, we first introduce an eMBB user clustering mechanism to balance the system throughput and computational complexity. Thereafter, we decompose the original problem into two subproblems, namely the scheduling problem of user selection and power allocation. We introduce a Gale-Shapley (GS) theory to solve the user selection problem, and a successive convex approximation (SCA) and a difference of convex (DC) programming to deal with the power allocation problem. Finally, an iterative algorithm is utilized to find the global solution with low computational complexity. Numerical results show the effectiveness of the proposed algorithms, and verify the proposed approach outperforms other baseline methods.