Exact ML criterion based on semidefinite relaxation for MIMO systems

Minjoon Kim, Jangyong Park, Kilhwan Kim, Jaeseok Kim

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this letter, we propose an exact maximum likelihood (ML) criterion based on semidefinite relaxation (SDR) in multiple-input multiple-output systems. Although a conventional SDR criterion for determining whether a symbol is the ML solution exists, its results cannot be guaranteed when noise is present. In place of the conventional criterion's positive semidefinite (PSD) discriminant, we propose a new, exact ML criterion based on the condition that all diagonal values are positive (PDV), a simple characteristic and necessary condition of PSD. The proposed criterion has a lower calculation complexity for testing than does a PSD and can ensure that the ML solution is always satisfactory.

Original languageEnglish
Article number6701202
Pages (from-to)343-346
Number of pages4
JournalIEEE Signal Processing Letters
Volume21
Issue number3
DOIs
Publication statusPublished - 2014 Mar 1

Fingerprint

Semidefinite Relaxation
MIMO Systems
MIMO systems
Maximum likelihood
Maximum Likelihood
Positive semidefinite
Multiple-input multiple-output (MIMO) Systems
Discriminant
Testing
Necessary Conditions

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Kim, Minjoon ; Park, Jangyong ; Kim, Kilhwan ; Kim, Jaeseok. / Exact ML criterion based on semidefinite relaxation for MIMO systems. In: IEEE Signal Processing Letters. 2014 ; Vol. 21, No. 3. pp. 343-346.
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Exact ML criterion based on semidefinite relaxation for MIMO systems. / Kim, Minjoon; Park, Jangyong; Kim, Kilhwan; Kim, Jaeseok.

In: IEEE Signal Processing Letters, Vol. 21, No. 3, 6701202, 01.03.2014, p. 343-346.

Research output: Contribution to journalArticle

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