Low-Rank Spatial Channel Estimation for Millimeter Wave Cellular Systems

Research output: Contribution to journalArticlepeer-review

Abstract

The tremendous bandwidth available in the millimeter wave frequencies above 10 GHz have made these bands an attractive candidate for next-generation cellular systems. However, reliable communication at these frequencies depends critically on beamforming with very high-dimensional antenna arrays. Estimating the channel sufficiently accurately to perform beamforming can be challenging due to both low coherence time and a large number of antennas. Also, the measurements used for channel estimation may need to be made with analog beamforming, where the receiver can 'look' in only one direction at a time. This paper presents a novel method for estimation of the receive-side spatial covariance matrix of a channel from a sequence of power measurements made in different angular directions. It is shown that maximum likelihood estimation of the covariance matrix reduces to a non-negative matrix completion problem. We show that the non-negative nature of the covariance matrix reduces the number of measurements required when the matrix is low-rank. The fast iterative methods are presented to solve the problem. Simulations are presented for both single-path and multi-path channels using models derived from real measurements in New York City at 28 GHz.

Original languageEnglish (US)
Article number7891613
Pages (from-to)2748-2759
Number of pages12
JournalIEEE Transactions on Wireless Communications
Volume16
Issue number5
DOIs
StatePublished - May 2017

Keywords

  • 5G
  • Millimeter wave radio
  • cellular systems
  • low-rank
  • spatial channel estimation

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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