Downlink Pilot Reduction for Massive MIMO Systems via Compressed Sensing

Jun Won Choi, Byonghyo Shim, Seok Ho Chang

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


This letter addresses a problem of downlink pilot allocation for massive multiple-input multiple-output (MIMO) systems. When a massive MIMO is employed in frequency division duplex (FDD) systems, significant amount of radio resources are dedicated to the transmission of downlink pilots. Such huge pilot overhead leads to a substantial loss in the maximum data throughput, which motivates us to reduce the number of pilots. In this letter, we propose a pilot reduction strategy based on compressed sensing techniques for orthogonal frequency division multiplexing systems. The pilots are randomly located in a low density manner over the time and frequency domain. To estimate the channels with such low density pilots, we propose a novel sparse channel estimation technique that exploits the common support of the consecutive channel impulse responses over the certain time duration. The evaluation shows that for a massive MIMO with 128 antennas, the proposed scheme achieves significant reduction of pilot overhead, while maintaining good channel estimation performance.

Original languageEnglish
Article number7229286
Pages (from-to)1889-1892
Number of pages4
JournalIEEE Communications Letters
Issue number11
Publication statusPublished - 2015 Nov 1


  • Channel estimation
  • Orthogonal frequency division multiplexing (OFDM)
  • compressed sensing
  • downlink pilot allocation
  • massive multiple-input multiple-output (MIMO)

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering


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