Low-Rank Spatial Channel Estimation for Millimeter Wave Cellular Systems

Research output: Contribution to journalArticle

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 1 2017

Fingerprint

Millimeter Wave
Cellular Systems
Channel Estimation
Channel estimation
Millimeter waves
Beamforming
Covariance matrix
Matrix Completion Problem
Multipath Channels
Antenna Arrays
Multipath propagation
Maximum likelihood estimation
Channel Model
Nonnegative Matrices
Iterative methods
Antenna arrays
Maximum Likelihood Estimation
Antenna
High-dimensional
Receiver

Keywords

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

ASJC Scopus subject areas

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

Cite this

Low-Rank Spatial Channel Estimation for Millimeter Wave Cellular Systems. / Eliasi, Parisa A.; Rangan, Sundeep; Rappaport, Theodore.

In: IEEE Transactions on Wireless Communications, Vol. 16, No. 5, 7891613, 01.05.2017, p. 2748-2759.

Research output: Contribution to journalArticle

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