Ordering aided Schnorr-Euchner sphere decoding with statistical pruning based on IRA for MIMO systems

  • Authors:
  • Junil Ahn;Heung-No Lee;Kiseon Kim

  • Affiliations:
  • School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea;School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea;School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

  • Venue:
  • APCC'09 Proceedings of the 15th Asia-Pacific conference on Communications
  • Year:
  • 2009

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Abstract

A Schnorr-Euchner sphere decoder (SESD) with increasing radii algorithm (IRA) named as the IRA-SESD and two ordering preprocessing strategies are considered in this paper. Statistical constrain radii (SCRs) are obtained from probabilistic distribution of path metric in order to statistically prune branches. Ordering preprocessing schemes are jointly applied to further reduce computational complexity of the IRA-SESD. This ordering aided IRA-SESD presents near-ML performance with low complexity. The proposed scheme has been evaluated by computer simulations for uncoded multiple-input multiple-output (MIMO) systems.