Training Signal Design for Correlated Massive MIMO Channel Estimation

Mojtaba Soltanalian, Mohammad Mahdi Naghsh, Nafiseh Shariati, Petre Stoica, Babak Hassibi

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

In this paper, we propose a new approach to the design of training sequences that can be used for an accurate estimation of multi-input multi-output channels. The proposed method is particularly instrumental in training sequence designs that deal with three key challenges: 1) arbitrary channel and noise statistics that do not follow specific models, 2) limitations on the properties of the transmit signals, including total power, per-antenna power, having a constant-modulus, discrete-phase, or low peak-to-average-power ratio, and 3) signal design for large-scale or massive antenna arrays. Several numerical examples are provided to examine the proposed method.
Original languageEnglish (US)
Pages (from-to)1135-1143
Number of pages9
JournalIEEE Transactions on Wireless Communications
Volume16
Issue number2
DOIs
StatePublished - Feb 2017
Externally publishedYes

ASJC Scopus subject areas

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

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