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An Improved Channel Estimation Method for Cell-Free Uplink Systems with Scalar Quantizers

  • Bumjun Kim
  • , Daesung Yu
  • , Seok Hwan Park

Research output: Contribution to conferenceConference paperpeer-review

Abstract

The channel estimation problem for the uplink of a cell-free multiple-input multiple-output (MIMO) system is studied. Standard approach for fronthaul quantization and channel estimation is reviewed first, and its limitation is discussed. To improve the channel estimation accuracy, it is proposed that, at each time instant, each radio unit (RU) quantizes a linear combination of the currently and previously received samples. To maximize the impact of linear combination, i.e., pre-processing, we tackle the problem of jointly optimizing the pilot sequences, pre-processing matrices and linear estimation filters with the goal of minimizing the sum of mean squared errors (MSEs) of channel gains. Numerical results validate the performance gains of the proposed channel estimation scheme with the optimized pre-processing matrices.

Original languageEnglish
Title of host publicationICTC 2020 - 11th International Conference on ICT Convergence
Subtitle of host publicationData, Network, and AI in the Age of Untact
PublisherIEEE Computer Society
Pages813-816
Number of pages4
ISBN (Electronic)9781728167589
DOIs
StatePublished - 2020.10.21
Event11th International Conference on Information and Communication Technology Convergence, ICTC 2020 - Jeju Island, Korea, Republic of
Duration: 2020.10.212020.10.23

Publication series

NameInternational Conference on ICT Convergence
Volume2020-October
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference11th International Conference on Information and Communication Technology Convergence, ICTC 2020
Country/TerritoryKorea, Republic of
CityJeju Island
Period20.10.2120.10.23

Keywords

  • Cell-free MIMO
  • channel estimation
  • scalar quantization
  • uplink

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems

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