Architectural optimizations for low-power K-best MIMO decoders

Sudip Mondal, Ahmed M. Eltawil, Khaled N. Salama

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Maximum-likelihood (ML) detection for higher order multiple-input-multiple-output (MIMO) systems faces a major challenge in computational complexity. This limits the practicality of these systems from an implementation point of view, particularly for mobile battery-operated devices. In this paper, we propose a modified approach for MIMO detection, which takes advantage of the quadratic-amplitude modulation (QAM) constellation structure to accelerate the detection procedure. This approach achieves low-power operation by extending the minimum number of paths and reducing the number of required computations for each path extension, which results in an order-of-magnitude reduction in computations in comparison with existing algorithms. This paper also describes the very-large-scale integration (VLSI) design of the low-power path metric computation unit. The approach is applied to a 4 × 4, 64-QAM MIMO detector system. Results show negligible performance degradation compared with conventional algorithms while reducing the complexity by more than 50%. © 2009 IEEE.
Original languageEnglish (US)
Pages (from-to)3145-3153
Number of pages9
JournalIEEE Transactions on Vehicular Technology
Issue number7
StatePublished - Sep 2009

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Manuscript received January 29, 2009. First published March 16, 2009; current version published August 14, 2009. This work was supported in part by the Center for Automation Technologies and Systems under a block grant from the New York State Foundation for Science, Technology, and Innovation and Grant 2006-IJ-CX-K044 from the National Institute of Justice under the Department of Justice. The review of this paper was coordinated by Dr. H. H. Nguyen.

ASJC Scopus subject areas

  • Automotive Engineering
  • Applied Mathematics
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Aerospace Engineering


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