Optimum Training for MIMO BPSK Transmission

Ayed M. Alrashdi, Ismail Ben Atitallah, Tarig Ballal, Christos Thrampoulidis, Anas Chaaban, Tareq Y. Al-Naffouri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In this paper, we derive an analytical expression for the bit error rate (BER) of binary phase shift keying (BPSK) symbols transmitted over a multiple-input multiple-output (MIMO) system under channel estimation errors. In this wireless communications system, the receiver uses the linear minimum mean squared error (LMMSE) estimator to estimate the channel matrix. The error in this estimation affects the following estimation that is used to recover the transmitted symbols. It is shown that the channel estimation error is Gaussian and hence the convex Gaussian min-max theorem (CGMT) can be applied to analyze the error of the signal estimation stage and finally obtain an expression for the BER. We use the BER expression to obtain the optimal pilot power allocation under a total transmit energy constraint. Numerical results show close matching between theory and simulations.

Original languageEnglish (US)
Title of host publication2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538635124
DOIs
StatePublished - Aug 24 2018
Event19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 - Kalamata, Greece
Duration: Jun 25 2018Jun 28 2018

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2018-June

Conference

Conference19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Country/TerritoryGreece
CityKalamata
Period06/25/1806/28/18

Keywords

  • MIMO
  • bit error rate
  • least squares
  • measurement matrix uncertainties
  • power allocation
  • regularized least squares

ASJC Scopus subject areas

  • Information Systems
  • Electrical and Electronic Engineering
  • Computer Science Applications

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