Cumulant Matrix-based Channel Estimation for Near-Field Massive MIMO Systems

Kyoungchan Seo, Gye Tae Gil, Girim Kwon, Songcheol Hong, Hyuncheol Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents an efficient channel estimation method for near-field massive multi-input multi-output (MIMO) systems. To estimate the channel parameters in terms of angles and ranges to the scatterers at the transmitter and receiver sides, we formulate the signal model for massive MIMO systems as a function of angle and range parameters. The signal model is then used to construct the fourth-order cumulant matrix, from which 2-dimensional (2D) multiple signal classification (MUSIC) pseudo-spectrums for the angles and ranges are derived. The effectiveness of the proposed algorithm is verified through simulation by comparing with the conventional channel estimation techniques.

Original languageEnglish
Title of host publicationICTC 2021 - 12th International Conference on ICT Convergence
Subtitle of host publicationBeyond the Pandemic Era with ICT Convergence Innovation
PublisherIEEE Computer Society
Pages1603-1608
Number of pages6
ISBN (Electronic)9781665423830
DOIs
StatePublished - 2021
Event12th International Conference on Information and Communication Technology Convergence, ICTC 2021 - Jeju Island, Korea, Republic of
Duration: 20 Oct 202122 Oct 2021

Publication series

NameInternational Conference on ICT Convergence
Volume2021-October
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference12th International Conference on Information and Communication Technology Convergence, ICTC 2021
Country/TerritoryKorea, Republic of
CityJeju Island
Period20/10/2122/10/21

Keywords

  • Channel estimation
  • high-order cumulant
  • massive MIMO
  • near-field communications
  • two-dimensional (2D) MUSIC

Fingerprint

Dive into the research topics of 'Cumulant Matrix-based Channel Estimation for Near-Field Massive MIMO Systems'. Together they form a unique fingerprint.

Cite this