Exact ML criterion based on semidefinite relaxation for MIMO systems

Minjoon Kim, Jangyong Park, Kilhwan Kim, Jaeseok Kim

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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
Issue number3
Publication statusPublished - 2014 Mar

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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