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Low complexity likelihood information generation for spatial-multiplexing MIMO signal detection

Publiceringsår: 2012
Språk: Engelska
Sidor: 607-617
Publikation/Tidskrift/Serie: IEEE Transactions on Vehicular Technology
Volym: 61
Nummer: 2
Dokumenttyp: Artikel i tidskrift
Förlag: IEEE--Institute of Electrical and Electronics Engineers Inc.


Abstract in Undetermined

Signal detection algorithms providing likelihood information

for coded spatial-multiplexing multiple-input multipleoutput

(MIMO) wireless communication system pose a critical

design challenge due to their prohibitively high computational

complexity. In this paper, we present a low-complexity soft-output

detection algorithm by adopting four implementation-friendly

algorithm-level improvements to the fixed-complexity sphere

decoder (FSD). More specifically, we introduce a reliabilitydependent

tree expansion approach and an on-demand listsize

reduction scheme for low-cost candidate list generation.

In terms of performance improvement, we apply an early bitflipping

strategy and utilize the l1-norm distance representation.

The algorithm is evaluated by computer simulations performed

over Rayleigh flat fading channels and computational complexity

analysis. Compared to the soft-output K-Best algorithm, the

proposed algorithm saves at least 60% of the computations for

detecting 4 x 4 64-QAM MIMO signal, and at the same time,

provides better detection performance, making it a promising

detection scheme for real-life hardware implementation.


  • Electrical Engineering, Electronic Engineering, Information Engineering
  • soft-output
  • Terms—Multiple-input multiple-output (MIMO) detection
  • spatial-multiplexing (SM)
  • log likelihood ratio (LLR)
  • fixed-complexity sphere decoder (FSD).


  • Digital ASIC-lup-obsolete
  • ISSN: 1939-9359

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