A new reduced complexity ML detection scheme for MIMO systems

Jin Sung Kim, Sung Hyun Moon, Inkyu Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

For multiple-input multiple-output (MIMO) systems, the optimum maximum likelihood (ML) detection requires tremendous complexity as the number of antennas or modulation level increases. This paper proposes a new algorithm which attains the ML performance with significantly reduced complexity. Based on the minimum mean square error (MMSE) criterion, the proposed scheme reduces the search space by excluding unreliable candidate symbols in data streams. Utilizing the probability metric which evaluates the reliability with the normalized likelihood functions of each symbol candidate, near optimal ML detection is made possible. A threshold parameter is introduced to balance a tradeoff between complexity and performance. Besides, we propose an efficient way of generating the log likelihood ratio (LLR) values which can be used for coded systems.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Communications, ICC 2009
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
Duration: 2009 Jun 142009 Jun 18

Publication series

NameIEEE International Conference on Communications
ISSN (Print)0536-1486

Other

Other2009 IEEE International Conference on Communications, ICC 2009
CountryGermany
CityDresden
Period09/6/1409/6/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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