ANALYSIS OF ITU-T AND ITU-R RECOMMENDATIONS ON FIFTH-GENERATION COMMUNICATION NETWORKS. PART I

Fifth Generation

Публикация представляет собой первую часть статьи,посвященной деятельности Международного союза электросвязи (МСЭ)в области стандартизации сетей связи пятого поколения и дальнейших перспективных разработок. Рассмотрены ключевые документы МСЭ-R, заложившие основу для исследований и разработки как радиоинтерфейсов, так и сетевой архитектуры сетей 5G/IMT-2020, ориентированной на качественно новые функции и услуги. Результаты нашли свое отражение в документах фокус-групп и в рекомендациях МСЭ-Т. This publication is the first part of an article devoted to the International Telecommunication Union (ITU) activity on the standardization of fifth-generation communication networks and further promising developments. The key ITU-R documents, which laid the foundation for research and development of both radio interfaces and the network architecture of 5G/IMT-2020 networks, focused on qualitatively new functions and services, are considered. The results are reflected in ITU-T focus group papers and ITU-T Recommendations.

ANALYSIS OF ITU-T AND ITU-R RECOMMENDATIONS ON FIFTH GENERATION COMMUNICATION NETWORKS. PART II

Труды НИИР ◽

10.34832/niir.2021.7.4.001 ◽

2021 ◽

Author(s):

Е.В. ТОНКИХ

Keyword(s):

Communication Networks ◽

Fifth Generation ◽

Network Functions

Во II части одноименной статьи,начало которой было опубликовано в сборнике «Труды НИИР», № 3'2021, рассматриваются результаты проводимой в рамках Международного союза электросвязи работы по стандартизации архитектуры сетей связи пятого поколения,а также требования,предъявляемые новыми сервисами и применениями к характеристикам этих сетей. Приводится обзор некоторых ключевых документов МСЭ, прежде всего Рекомендаций МСЭ-Т по требованиям к сетям с учетом дальнейшей виртуализации (софтверизации)многих сетевых функций сетей 5G/IMT-2020. In the second part of the article of the same name, that was published in the collection "Proceedings if the NIIR", No. 3'2021, the results of the work of the International Telecommunication Union to standardize the architecture of fifth-generation communication networks, as well as the requirements imposed by new services and applications to the characteristics of these networks are considered. An overview of some key ITU documents is provided, primarily the ITU-T Recommendations on network requirements, taking into account the further virtualization (softwarization) of many network functions of 5G / IMT-2020 networks.

A line-of-sight channel model for the 100–450 gigahertz frequency band

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01974-8 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Joonas Kokkoniemi ◽

Janne Lehtomäki ◽

Markku Juntti

Keyword(s):

Channel Model ◽

Full Range ◽

Line Of Sight ◽

Absorption Loss ◽

Radio Communication ◽

Fifth Generation ◽

Proposed Model ◽

Actual Response

AbstractThis paper documents a simple parametric polynomial line-of-sight channel model for 100–450 GHz band. The band comprises two popular beyond fifth generation (B5G) frequency bands, namely, the D band (110–170 GHz) and the low-THz band (around 275–325 GHz). The main focus herein is to derive a simple, compact, and accurate molecular absorption loss model for the 100–450 GHz band. The derived model relies on simple absorption line shape functions that are fitted to the actual response given by complex but exact database approach. The model is also reducible for particular sub-bands within the full range of 100–450 GHz, further simplifying the absorption loss estimate. The proposed model is shown to be very accurate by benchmarking it against the exact response and the similar models given by International Telecommunication Union Radio Communication Sector. The loss is shown to be within ±2 dBs from the exact response for one kilometer link in highly humid environment. Therefore, its accuracy is even much better in the case of usually considered shorter range future B5G wireless systems.

Enabling Heterogeneous IoT Networks over 5G Networks with Ultra-Dense Deployment—Using MEC/SDN

Electronics ◽

10.3390/electronics10080910 ◽

2021 ◽

Vol 10 (8) ◽

pp. 910

Author(s):

Abdelhamied A. Ateya ◽

Abeer D. Algarni ◽

Monia Hamdi ◽

Andrey Koucheryavy ◽

Naglaa. F. Soliman

Keyword(s):

5G Networks ◽

System Availability ◽

Network Availability ◽

Fifth Generation ◽

Massive Number ◽

Iot Platforms ◽

3Rd Generation Partnership Project ◽

The Internet Of Things

The Internet of things (IoT) is the third evolution of the traditional Internet that enables interaction and communication among machines. Many IoT platforms and networks have been developed, and recently, market sectors have started to develop specific IoT applications and services. Integrating heterogeneous IoT networks with the existing ones, mainly with the cellular networks, is a great demand. IoT represents one of the main use cases of the fifth-generation (5G) cellular system as announced by the 3rd Generation Partnership Project (3GPP) and the International Telecommunication Union (ITU). Integrating IoT networks with 5G networks face many challenges related to dense deployment and a massive number of expected connected devices. Thus, IoT network availability and scalability are the main requirements that should be achieved. To this end, this work provides a framework for integrating heterogeneous IoT networks with the 5G networks. The proposed system considers dense deployment and system scalability and availability requirements as announced by ITU and 3GPP. Our proposed structure deploys three main communication paradigms; mobile edge computing (MEC), device-to-device communications (D2D), and software-defined networking (SDN). Our proposed system is evaluated over a reliable environment for various deployment scenarios, and the results validate the proposed structure. The proposed IoT/5G reduces the percentage of blocked tasks by an average of 30% than other traditional IoT networks. This increases the overall system availability and scalability since IoT networks can have more devices and tasks than existing IoT networks. Furthermore, our proposed structure reduces the overall consumed energy by an average of 20% than existing IoT networks, which is an effective metric for IoT networks.

5G Ultra-Reliable Low-Latency Communication Implementation Challenges and Operational Issues with IoT Devices

Electronics ◽

10.3390/electronics8090981 ◽

2019 ◽

Vol 8 (9) ◽

pp. 981 ◽

Cited By ~ 22

Author(s):

Siddiqi ◽

Yu ◽

Joung

Keyword(s):

Low Latency ◽

Implementation Challenges ◽

Research Areas ◽

Fifth Generation ◽

Machine Type Communications ◽

Reliable Communications ◽

Iot Devices ◽

Operational Issues

To meet the diverse industrial and market demands, the International Telecommunication Union (ITU) has classified the fifth-generation (5G) into ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). Researchers conducted studies to achieve the implementation of the mentioned distributions efficiently, within the available spectrum. This paper aims to highlight the importance of URLLC in accordance with the approaching era of technology and industry requirements. While highlighting a few implementation issues of URLLC, concerns for the Internet of things (IoT) devices that depend on the low latency and reliable communications of URLLC are also addressed. In this paper, the recent progress of 3rd Generation Partnership Project (3GPP) standardization and the implementation of URLLC are included. Finally, the research areas that are open for further investigation in URLLC implementation are highlighted, and efficient implementation of URLLC is discussed.

Attenuation by a Human Body and Trees as well as Material Penetration Loss in 26 and 39 GHz Millimeter Wave Bands

International Journal of Antennas and Propagation ◽

10.1155/2017/2961090 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8 ◽

Cited By ~ 5

Author(s):

Qi Wang ◽

Xiongwen Zhao ◽

Shu Li ◽

Mengjun Wang ◽

Shaohui Sun ◽

...

Keyword(s):

Human Body ◽

University Campus ◽

Channel Sounder ◽

Uniform Theory Of Diffraction ◽

Fifth Generation ◽

Radio Systems ◽

Itu Model ◽

Penetration Loss

This paper investigates the attenuation by a human body and trees as well as material penetration loss at 26 and 39 GHz by measurements and theoretical modeling work. The measurements were carried out at a large restaurant and a university campus by using a time domain channel sounder. Meanwhile, the knife-edge (KE) model and one-cylinder and two-cylinder models based on uniform theory of diffraction (UTD) are applied to model the shape of a human body and predict its attenuation in theory. The ITU (International Telecommunication Union) and its modified models are used to predict the attenuation by trees. The results show that the upper bound of the KE model is better to predict the attenuation by a human body compared with UTD one-cylinder and two-cylinder models at both 26 and 39 GHz. ITU model overestimates the attenuation by willow trees, and a modified attenuation model by trees is proposed based on our measurements at 26 GHz. Penetration loss for materials such as wood and glass with different types and thicknesses is measured as well. The measurement and modeling results in this paper are significant and necessary for simulation and planning of fifth-generation (5G) mm-wave radio systems in ITU recommended frequency bands at 26 and 39 GHz.

ITU/WMO/UNEP Focus Group on AI for Natural Disaster Management: Introduction and call for participation

10.5194/egusphere-egu21-12791 ◽

2021 ◽

Author(s):

Monique Kuglitsch

Keyword(s):

Focus Group ◽

Natural Disaster ◽

Disaster Management ◽

United Nations Environment Programme ◽

Spatiotemporal Scales ◽

Multi Stakeholder ◽

Natural Disaster Management ◽

Nations Environment

<p>The International Telecommunication Union (ITU), World Meteorological Organization (WMO), and United Nations Environment Programme (UNEP) have recently partnered to establish the Focus Group on Artificial Intelligence for Natural Disaster Management (FG-AI4NDM). FG-AI4NDM is exploring the potential of AI-based algorithms to support data collection and handling, to improve modeling (i.e., reconstructions, forecasts, and projections) across spatiotemporal scales through extracting complex patterns (and gaining insights) from a growing volume of geospatial data, and to provide effective communication. To achieve these objectives, FG-AI4NDM is building an interdisciplinary, multi-stakeholder, and international community to explore specific natural disaster use cases. Special effort is made to support participation from low- and mid-income countries and those countries shown to be particularly impacted by these types of events. Here, we will explore: what is an ITU focus group, what are the objectives and planned deliverables of FG-AI4NDM, what progress has been made since its inception, and how members of the geoscience community can become involved.</p>

The graph neural networking challenge

ACM SIGCOMM Computer Communication Review ◽

10.1145/3477482.3477485 ◽

2021 ◽

Vol 51 (3) ◽

pp. 9-16

Author(s):

José Suárez-Varela ◽

Miquel Ferriol-Galmés ◽

Albert López ◽

Paul Almasan ◽

Guillermo Bernárdez ◽

...

Keyword(s):

Machine Learning ◽

Computer Networks ◽

Real World ◽

Large Scale ◽

Lessons Learned ◽

Educational Resources ◽

Global Competition ◽

Broad Audience

During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge", an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020". We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.

Measuring Key Quality Indicators in Cloud Gaming: Framework and Assessment Over Wireless Networks

Sensors ◽

10.3390/s21041387 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1387

Author(s):

Oswaldo Sebastian Peñaherrera-Pulla ◽

Carlos Baena ◽

Sergio Fortes ◽

Eduardo Baena ◽

Raquel Barco

Keyword(s):

Communication Networks ◽

Mobile Networks ◽

Video Game ◽

Know How ◽

Fifth Generation ◽

New Generation ◽

Graphics Rendering ◽

The Impact

Cloud Gaming is a cutting-edge paradigm in the video game provision where the graphics rendering and logic are computed in the cloud. This allows a user’s thin client systems with much more limited capabilities to offer a comparable experience with traditional local and online gaming but using reduced hardware requirements. In contrast, this approach stresses the communication networks between the client and the cloud. In this context, it is necessary to know how to configure the network in order to provide service with the best quality. To that end, the present work defines a novel framework for Cloud Gaming performance evaluation. This system is implemented in a real testbed and evaluates the Cloud Gaming approach for different transport networks (Ethernet, WiFi, and LTE (Long Term Evolution)) and scenarios, automating the acquisition of the gaming metrics. From this, the impact on the overall gaming experience is analyzed identifying the main parameters involved in its performance. Hence, the future lines for Cloud Gaming QoE-based (Quality of Experience) optimization are established, this way being of configuration, a trendy paradigm in the new-generation networks, such as 4G and 5G (Fourth and Fifth Generation of Mobile Networks).

Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

Electronics ◽

10.3390/electronics10020169 ◽

2021 ◽

Vol 10 (2) ◽

pp. 169

Author(s):

Sherief Hashima ◽

Basem M. ElHalawany ◽

Kohei Hatano ◽

Kaishun Wu ◽

Ehab Mahmoud Mohamed

Keyword(s):

Machine Learning ◽

Network Architecture ◽

D2d Communication ◽

Neighbor Discovery ◽

Research Directions ◽

Fifth Generation ◽

Research Activities ◽

Comprehensive Survey ◽

Network Overhead

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

THE ROLE OF HARMONIZATION OF ACTIVITIES TO IMPROVE THE RATING OF RUSSIA IN THE INTERNATIONAL STATISTICAL COMPARISONS IN TELECOMMUNICATIONS AND ICT

Электросвязь ◽

10.34832/elsv.2020.7.6.008 ◽

2020 ◽

Author(s):

Н.П. РЕЗНИКОВА ◽

Г.С. АРТЕМЬЕВА ◽

Д.В. КАЛЮГА

Keyword(s):

Sustainable Development ◽

Sustainable Development Goals ◽

The Sustainable Development ◽

Development Goals ◽

The Russian Federation ◽

Ict Development ◽

The Impact

Представлены основные направления для поиска путей улучшения рейтинга Российской Федерации в международных статистических сопоставлениях в сфере электросвязи/ИКТ с учетом необходимости гармонизации разнообразных направлений деятельности, связанных с оценкой влияния электросвязи/ИКТ на достижение Целей устойчивого развития, а также с появлением Нового индекса Международного союза электросвязи (МСЭ) взамен Индекса развития ИКТ(IDI). OThe main directions for finding ways to improve the rating of the Russian Federation in international statistical comparisons in the field of telecommunications/ICT are presented, taking into account the need to harmonize various activities related to assessing the impact of telecommunications/ICTs on achieving the sustainable development goals, as well as the advent of the new International Telecommunication Union Index instead of the ICT Development Index (IDI).