Near-ML soft-MIMO detector with reduced complexity

Kilhwan Kim, Yunho Jung, Seongjoo Lee, Jaeseok Kim

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

Abstract

This paper proposes a soft-detector with near-maximum likelihood (ML) performance in multiple-input multiple-output (MIMO) systems. The proposed detector performs an initial detection for candidate vectors by applying a low complexity channel matrix ordering. The detection order then is diversified to extend the list of candidates, from which high-quality soft-output can be generated. In addition, a method for reducing overhead from the diversification of the detection order is presented. Simulation results on a 4×4 system with a convolutional turbo code of 5/6 rate show that the proposed detector can approximate the performance of the soft-ML detector but its complexity is approximately 46% of a reference detector [5].

Original languageEnglish
Title of host publicationIEEE TENCON 2012
Subtitle of host publicationSustainable Development Through Humanitarian Technology
DOIs
Publication statusPublished - 2012
Event2012 IEEE Region 10 Conference: Sustainable Development Through Humanitarian Technology, TENCON 2012 - Cebu, Philippines
Duration: 2012 Nov 192012 Nov 22

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON

Other

Other2012 IEEE Region 10 Conference: Sustainable Development Through Humanitarian Technology, TENCON 2012
CountryPhilippines
CityCebu
Period12/11/1912/11/22

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Kim, K., Jung, Y., Lee, S., & Kim, J. (2012). Near-ML soft-MIMO detector with reduced complexity. In IEEE TENCON 2012: Sustainable Development Through Humanitarian Technology [6412263] (IEEE Region 10 Annual International Conference, Proceedings/TENCON). https://doi.org/10.1109/TENCON.2012.6412263