• 제목/요약/키워드: Mobile backhaul

검색결과 52건 처리시간 0.027초

Implementation of Radio Access Network for Mobile Backhaul Network (이동 백홀 네트워크용 Radio Access Network 구현)

  • Park, Chun-Kwan;Song, Han-Young;Jeon, Byung-Chun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제10권6호
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    • pp.77-84
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    • 2010
  • This paper aims to implement RAN(Radio Access Network) transmission system that can reduce the transmission cost by installing between mobile base station and base station controller. This system can reduce the number of transmission links by sharing the transmission link that the mobile communication stations of various generation use separately. This also can classify the traffics non-sensitive to delay time, and then transfer them through Ethernet/IP network.

Fronthaul Technology Trends for 5G Mobile Communications (5G 이동통신을 위한 프론트홀 기술 동향)

  • Oh, D.S.;Lyu, D.S.;Lee, H.
    • Electronics and Telecommunications Trends
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    • 제32권5호
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    • pp.97-106
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    • 2017
  • The introduction of new access technologies in 5G radio networks has had a considerable impact on the design of transport networks. Research activities are underway on new transport technologies in both the wireless and optical domains to support 5G transport. This paper provides an overview of the concept and requirements of a fronthaul. We also discuss the research activities of a new fronthaul interface for future 5G networks, a 5G integrated fronthaul/backhaul transport network (5G-Crosshaul), a next-generation fronthaul interface (NGFI), a mobile xhaul network (MXN), and a next-generation mobile fronthaul architecture with multi-IF carrier transmission scheme.

A Study on Spatial Combining power Amplifiers for Backhaul of 5G cellular systems (5세대 이동통신 백홀용 공간 결합 전력 증폭기에 관한 연구)

  • Ki, Hyeon-Cheol
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제16권4호
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    • pp.21-26
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    • 2016
  • In this paper we proposed a new structure of spatial combining power amplifier working in 60GHz global unlicensed band(56-64GHz) for the backhaul in the 5 generation mobile systems. The proposed structure is suitable to realize an antipodal finline transition in millimeter wave band, in which the size of cross section of waveguide becomes about a few mm ${\times}$ a few mm, due to its compact structure of the transition and shows effective heat sinking characteristics because its ground plane can contact to the body metal. However, the HFSS simulation results showed the return loss improvement by 1.27dB and the same insertion loss of -1.65dB compared with the conventional structure, which said nevertheless the advantages, there was no deterioration in the performance.

Introducing the Latest 3GPP Specifications and their Potential for Future AMI Applications

  • Koumadi, Koudjo M.;Park, Byong-seok;Myoung, Nogil
    • KEPCO Journal on Electric Power and Energy
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    • 제2권2호
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    • pp.245-251
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    • 2016
  • Despite the exponential throughput improvement in mobile communications systems, their ability to satisfy requirements of state-of-the-art and future applications of advanced metering infrastructure (AMI) is still under investigation. Challenges are mainly due to the inadequacy of third generation partnership project (3GPP) networks to support large amounts of devices simultaneously, while the number of AMI end-devices and the frequency of their data transmission increase with new AMI-based applications. In this introductory survey, innovative and future AMI applications and their communication requirements are first reviewed. Then, we identify challenges of 3GPP long term evolution (LTE) in enabling future AMI applications. More importantly, the latest improvements to LTE-A standard release 12 and 13 are reviewed and analyzed with regards to their potential to improve the quality of LTE-enabled AMI. It is found that 3GPP enhancements on machine type communications (MTC) standards will significantly enhance AMI communications. Beyond MTC specifications, non-MTC-specific enhancements such as carrier aggregation and multi-connectivity for user equipment will also contribute greatly to improving reliability and availability of AMI devices. The paper's focus is towards improved backhaul support for innovative and future AMI applications, beyond traditional automatic meter reading.

Intelligent Massive Traffic Handling Scheme in 5G Bottleneck Backhaul Networks

  • Tam, Prohim;Math, Sa;Kim, Seokhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권3호
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    • pp.874-890
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    • 2021
  • With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

Big Data Meets Telcos: A Proactive Caching Perspective

  • Bastug, Ejder;Bennis, Mehdi;Zeydan, Engin;Kader, Manhal Abdel;Karatepe, Ilyas Alper;Er, Ahmet Salih;Debbah, Merouane
    • Journal of Communications and Networks
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    • 제17권6호
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    • pp.549-557
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    • 2015
  • Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

Recent R&D Trends in Wireless Network Technology based on UAV-assisted FSO Technique (UAV 기반 FSO 무선통신 네트워크 기술 동향)

  • Yeo, C.I.;Heo, Y.S.;Ryu, J.H.;Park, S.W.;Kim, S.C.;Kang, H.S.;Lee, G.H.
    • Electronics and Telecommunications Trends
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    • 제35권2호
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    • pp.38-49
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    • 2020
  • In recent years, the unmanned aerial vehicle (UAV) assisted mobile free space optical (FSO) communication technique has attracted considerable attention regarding its aims to provide improved communication conditions for fixed-to-fixed FSO network and promising fronthaul and backhaul solutions for 5G+ wireless networks. This can be attributed to its outstanding advantages such as fast deployment and flexible network configuration. The UAV-assisted mobile FSO system can be used to provide cost-effective internet services in rural and remote areas and in hotspot areas that are characterized by increased data traffic. Additionally, it can be used to provide secure communication services under emergency circumstances. In this report, we review recent R&D trends in wireless network technology employing the UAV-assisted mobile FSO technique and key technologies for mobile FSO wireless networks. Furthermore, we introduce drone-based mobile FSO terminals and control systems that we have developed.

Joint Load Balancing and Radio Resource Management in Cross Layer Architecture

  • Kim, Cheol-Seung;Ryu, Kyu-Tea
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.205-206
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    • 2008
  • We propose load balancing algorithm based on cross layer designing for MIMO OFDM system. When there are many users using data service, base station(BS) should distribute traffic. Moreover, cross layer design gives benefit managing radio resource and network bandwidth management. Proposed cross layer load balancing technique manages both BS's bandwidth allocation and MS’s power control. One BS request bandwidth to other BSes and other BSes reduce each bandwidth. And BSes reduce power of sub carriers for reserving available bandwidth of backhaul. MSes that didn't get service can be served by obtaining bandwidth from other BSes. The simulation result shows more users can be served and cell throughput was increased

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Cooperative Content Caching and Distribution in Dense Networks

  • Kabir, Asif
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권11호
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    • pp.5323-5343
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    • 2018
  • Mobile applications and social networks tend to enhance the need for high-quality content access. To address the rapid growing demand for data services in mobile networks, it is necessary to develop efficient content caching and distribution techniques, aiming at significantly reduction of redundant content transmission and thus improve content delivery efficiency. In this article, we develop optimal cooperative content cache and distribution policy, where a geographical cluster model is designed for content retrieval across the collaborative small cell base stations (SBSs) and replacement of cache framework. Furthermore, we divide the SBS storage space into two equal parts: the first is local, the other is global content cache. We propose an algorithm to minimize the content caching delay, transmission cost and backhaul bottleneck at the edge of networks. Simulation results indicates that the proposed neighbor SBSs cooperative caching scheme brings a substantial improvement regarding content availability and cache storage capacity at the edge of networks in comparison with the current conventional cache placement approaches.

Deep Learning based Loss Recovery Mechanism for Video Streaming over Mobile Information-Centric Network

  • Han, Longzhe;Maksymyuk, Taras;Bao, Xuecai;Zhao, Jia;Liu, Yan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권9호
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    • pp.4572-4586
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    • 2019
  • Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.