A low-complexity near-ml decoding technique via reduced dimension list stack algorithm

Won Choi Jun, Byonghyo Shim, Andrew C. Singer, Ik Cho Nam

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

4 Citations (Scopus)

Abstract

In this paper, we propose a near maximum likelihood (ML) decoding technique, which reduces the computational complexity of the exact ML decoding algorithm. The computations needed for the tree search in the ML decoding is simplified by reducing the dimension of the search space prior to the tree search. In order to compensate performance loss due to the dimension reduction, a list stack algorithm (LSA) is considered, which produces a list of the top K closest points. The combination of both approaches, called reduced dimension list stack algorithm (RD-LSA), is shown to provide flexibility and offers a performance-complexity trade-off. Simulations performed for V-BLAST transmission demonstrate that significant complexity reduction can be achieved compared to the sphere decoding algorithm (SDA) while keeping the performance loss below an acceptable level.

Original languageEnglish
Title of host publicationSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop
Pages41-44
Number of pages4
DOIs
Publication statusPublished - 2008 Oct 6
EventSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop - Darmstadt, Germany
Duration: 2008 Jul 212008 Jul 23

Other

OtherSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop
CountryGermany
CityDarmstadt
Period08/7/2108/7/23

Fingerprint

Decoding
Maximum likelihood
Trees (mathematics)
Computational complexity

Keywords

  • Dimension reduction
  • Maximum likelihood
  • MIMO
  • Sphere decoding
  • Tree search

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Jun, W. C., Shim, B., Singer, A. C., & Nam, I. C. (2008). A low-complexity near-ml decoding technique via reduced dimension list stack algorithm. In SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop (pp. 41-44). [4606820] https://doi.org/10.1109/SAM.2008.4606820

A low-complexity near-ml decoding technique via reduced dimension list stack algorithm. / Jun, Won Choi; Shim, Byonghyo; Singer, Andrew C.; Nam, Ik Cho.

SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop. 2008. p. 41-44 4606820.

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

Jun, WC, Shim, B, Singer, AC & Nam, IC 2008, A low-complexity near-ml decoding technique via reduced dimension list stack algorithm. in SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop., 4606820, pp. 41-44, SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, Darmstadt, Germany, 08/7/21. https://doi.org/10.1109/SAM.2008.4606820
Jun WC, Shim B, Singer AC, Nam IC. A low-complexity near-ml decoding technique via reduced dimension list stack algorithm. In SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop. 2008. p. 41-44. 4606820 https://doi.org/10.1109/SAM.2008.4606820
Jun, Won Choi ; Shim, Byonghyo ; Singer, Andrew C. ; Nam, Ik Cho. / A low-complexity near-ml decoding technique via reduced dimension list stack algorithm. SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop. 2008. pp. 41-44
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