• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.8-19
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• 2019

Since their emergence in 2007, smart phones have advanced up to the point that 5G mobile communication in 2019 started to be commercialized. Accordingly, now it is possible to share 3D modeling files and collaborate by means of a mobile web. As the recently commercialized 5G mobile communication network is so useful in sharing 3D modeling files and collaborating that even large-size geometry files can be transmitted at ultra high speed with ultra low transfer delay. We examines characteristics of major 3D file formats such as STL, OBJ, FBX, and glTF and compares the existing 4G LTE (Long Term Evolution) network with the 5G NR (New Radio) mobile communication network. The loading time and packets of each format were measured depending on the mobile web browser environments. We shows that in comparison with 4G LTE, the loading time of STL and OBJ file formats were reduced as much as 6.55 sec and 9.41 sec, respectively in the 5G NR and Chrome browsers. The glTF file format showed the most efficient performance in all of the 4G/5G mobile communication networks, Chrome, and Edge browsers. In the case of STL and OBJ, the traffic was relatively excessive in 5G NR and Edge browsers. The findings of this study are expected to be utilized to develop a 3D file format that reduces the loading time in a mobile web environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.549-559
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• 2023

As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.896-914
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• 2020

With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

• Convergence Security Journal
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• v.20 no.3
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• pp.47-52
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• 2020

The introduction of virtualization technology in the broadcasting field is actively progressing broadcasting service automation and intelligence based on the effective operation of IT resources throughout the broadcasting industry ecosystem. In recent years, there is increasing interest in increasing the flexibility of various broadcasting resources and increasing the efficiency of interworking with other networks through network virtualization of the broadcasting network infrastructure. The fundamental transformation from the broadcasting network to the IP paradigm is facing a situation where it is necessary to solve various problems for the effective interworking of Internet-based service platforms and 5G networks and the development of new convergence services. In other words, for organic and effective interworking with the next-generation broadcasting network represented by ATSC 3.0, a mobile communication network represented by 5G, and the Internet, a number of difficulties must be solved. In this paper, the basic technology and status for the convergence of ATSC 3.0 broadcasting network and mobile communication network represented by 5G was examined, and a plan for the ATSC 3.0 broadcasting network and 5G network to interwork with each other as a network was described.

• ETRI Journal
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• v.37 no.5
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• pp.856-866
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• 2015

A heterogeneous network (HetNet) is a network topology composed by deploying multiple HetNets under the coverage of macro cells (MCs). It can improve network throughput, extend cell coverage, and offload network traffic; for example, the network traffic of a 5G mobile communications network. A HetNet involves a mix of radio technologies and various cell types working together seamlessly. In a HetNet, coordination between MCs and small cells (SCs) has a positive impact on the performance of the networks contained within, and consequently on the overall user experience. Therefore, to improve user-perceived service quality, HetNets require high-efficiency network protocols and enhanced radio technologies. In this paper, we introduce a 5G HetNet comprised of MCs and both fixed and mobile SCs (mSCs). The featured mSCs can be mounted on a car, bus, or train and have different characteristics to fixed SCs (fSCs). In this paper, we address the technical challenges related to mSCs. In addition, we analyze the network performance under two HetNet scenarios-MCs and fSCs, and MCs and mSCs.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.50-56
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• 2021

Due to the recent increase in the mobile streaming market, mobile traffic is increasing exponentially. IMT-2020, named as the next generation mobile communication standard by ITU, is called the 5th generation mobile communication (5G), and is a technology that satisfies the data traffic capacity, low latency, high energy efficiency, and economic efficiency compared to the existing LTE (Long Term Evolution) system. 5G implements this technology by utilizing a high frequency band, but there is a problem of path loss due to the use of a high frequency band, which is greatly affected by system performance. In this paper, small cell technology was presented as a solution to the high frequency utilization of 5G mobile communication system, and furthermore, the system performance was improved by applying machine learning technology to macro communication and small cell communication method decision. It was found that the system performance was improved due to the technical application and the application of machine learning techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.13-24
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• 2021

Industrial networks has been developing various technologies from fieldbus technology to industrial Ethernet and time-sensitive networking. The industry expects that the 5G mobile network will solve the diverse and highly specific industrial site requirements. Accordingly, 3GPP has been developing standard functions to provide ultra-high reliability, ultra-high speed, ultra-connection, and ultra-low latency services, and 3GPP Rel-16 began developing ultra-low latency and ultra-high reliability communication functions for 5G mobile networks to support vertical industries. In this paper, we show the related standardization trends and requirements to apply industrial IoT service scenarios to 5G mobile networks, and in particular, we introduce 5G system features and extended 5G system architecture to provide time sensitive communication and time synchronization services.

• Electronics and Telecommunications Trends
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• v.38 no.2
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• pp.26-35
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• 2023

Energy efficiency is an important factor toward sustainable future mobile network systems. As the size of the 5G mobile network system increases, the consumption and costs of energy increase. Accordingly, energy-saving optimization has become a major process in network systems, and various related technologies for energy saving are being developed. We provide a brief review of the technical trends in energy saving in 3GPP 5G & 5G Advanced systems and O-RAN systems. We focus on power models and energy-saving technologies in various resource domains of 3GPP 5G & 5G Advanced systems and energy-saving use cases of O-RAN systems.

• ETRI Journal
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• v.42 no.5
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• pp.721-733
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• 2020

Recently, there is an increasing demand for ultra-low-latency (ULL) services such as factory automation, autonomous driving, and telesurgery that must meet an end-to-end latency of less than 10 ms. Fifth-generation (5G) New Radio guarantees 0.5 ms one-way latency, so the feasibility of ULL services is higher than in previous mobile communications. However, this feasibility ensures performance at the radio access network level and requires an innovative 5G network architecture for end-to-end ULL across the entire 5G system. Hence, we survey in detailed two the 3rd Generation Partnership Party (3GPP) standardization activities to ensure low latency at network level. 3GPP standardizes mobile edge computing (MEC), a low-latency solution at the edge network, in Release 15/16 and is standardizing time-sensitive communication in Release 16/17 for interworking 5G systems and IEEE 802.1 time-sensitive networking (TSN), a next-generation industry technology for ensuring low/deterministic latency. We developed a 5G system based on 3GPP Release 15 to support MEC with a potential sub-10 ms end-to-end latency in the edge network. In the near future, to provide ULL services in the external network of a 5G system, we suggest a 5G-IEEE TSN interworking system based on 3GPP Release 16/17 that meets an end-to-end latency of 2 ms.