System-level Data Rate Evaluation for IMT-2020 Urban Micro Channel Model

Inseok Lee, Seong-Jun Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

ITU-R has defined IMT-2020 as a new standard name for fifth generation mobile systems and has set the minimum performance requirements and evaluation methodologies of IMT-2020. IMT-2020 systems will be the mobile systems that include new radio interface which support the new capabilities of systems beyond IMT-Advanced. In particular, the data rate of IMT-2020 is expected to be 10 times to 20 times larger compared to IMT-Advanced for enhanced Mobile Broadband. In order to achieve the IMT-2020 data rate requirements, the use of mmWave band and micro-cell deployment is essential. In this paper, we evaluate the theoretically expected data rate of urban micro channel model by downlink 2×2 MIMO system level simulation. When the micro-cells are deployed over the macro-cells layout, the expected data rate is about 3.9Gbits/s, which is 5 times larger than only macro-cell scenario.

Original languageEnglish
Title of host publication9th International Conference on Information and Communication Technology Convergence
Subtitle of host publicationICT Convergence Powered by Smart Intelligence, ICTC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages876-879
Number of pages4
ISBN (Electronic)9781538650400
DOIs
Publication statusPublished - 2018 Nov 16
Event9th International Conference on Information and Communication Technology Convergence, ICTC 2018 - Jeju Island, Korea, Republic of
Duration: 2018 Oct 172018 Oct 19

Other

Other9th International Conference on Information and Communication Technology Convergence, ICTC 2018
Country/TerritoryKorea, Republic of
CityJeju Island
Period18/10/1718/10/19

Keywords

  • Data rate
  • micro-cell
  • MIMO
  • mmWave
  • System Level Simulation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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