Compressive sensing based pilot reduction technique for massive MIMO systems

Jun Won Choi, Byonghyo Shim

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

4 Citations (Scopus)


Massive multi-input multi-output (MIMO) technique deploys a number of transmit antennas in base-station (BS) to support large number of users and high data throughput. Since BS needs to acquire channel state information from all transmit antennas, substantial amount of downlink pilot signals is required. In this paper, we suggest a new downlink pilot allocation strategy, inspired by the compressed sensing principle, that reduces the density of the pilot significantly. Key observation in the proposed approach is that the sparse structure of the channel impulse response (CIR) tends to change slower than the OFDM symbol rate. Through computer simulations, we show that the proposed scheme outperforms the conventional compressed sensing methods, achieving the performance bound provided by the Oracle-based Kalman smoother.

Original languageEnglish
Title of host publication2015 Information Theory and Applications Workshop, ITA 2015 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Print)9781479971954
Publication statusPublished - 2015 Oct 27
Externally publishedYes
EventInformation Theory and Applications Workshop, ITA 2015 - San Diego, United States
Duration: 2015 Feb 12015 Feb 6


OtherInformation Theory and Applications Workshop, ITA 2015
Country/TerritoryUnited States
CitySan Diego


  • OFDM
  • Q measurement
  • Signal to noise ratio

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems


Dive into the research topics of 'Compressive sensing based pilot reduction technique for massive MIMO systems'. Together they form a unique fingerprint.

Cite this