Reducing the complexity of LDPC decoding algorithms: An optimization-oriented approach

This paper presents a structured optimization framework for reducing the computational complexity of LDPC decoders. Subject to specified performance constraints and adaptive to environment conditions, the proposed framework leverages the adjustable performance-complexity tradeoffs of the decoder to...

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Published in:IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops (Print) pp. 861 - 866
Main Authors: Sarajlic, Muris, Liang Liu, Edfors, Ove
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2014
Subjects:
Algorithm design and analysis
Complexity theory
Convergence
Decoding
Iterative decoding
Signal to noise ratio
ISSN:2166-9570
Online Access:Get full text
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Abstract This paper presents a structured optimization framework for reducing the computational complexity of LDPC decoders. Subject to specified performance constraints and adaptive to environment conditions, the proposed framework leverages the adjustable performance-complexity tradeoffs of the decoder to deliver satisfying performance with minimum computational complexity. More specifically, two constraint scenarios are studied: the "good-enough" performance and "as-good-as-possible performance". Moreover, we also investigate the effects of different degrees of freedom in performance-complexity tradeoff adjustments. The effectiveness of the proposed method has been verified by simulating a set of LDPC codes used in IEEE 802.11 and IEEE 802.16 standards. Computational complexity reductions of up to 35% have been observed.
AbstractList This paper presents a structured optimization framework for reducing the computational complexity of LDPC decoders. Subject to specified performance constraints and adaptive to environment conditions, the proposed framework leverages the adjustable performance-complexity tradeoffs of the decoder to deliver satisfying performance with minimum computational complexity. More specifically, two constraint scenarios are studied: the "good-enough" performance and "as-good-as-possible performance". Moreover, we also investigate the effects of different degrees of freedom in performance-complexity tradeoff adjustments. The effectiveness of the proposed method has been verified by simulating a set of LDPC codes used in IEEE 802.11 and IEEE 802.16 standards. Computational complexity reductions of up to 35% have been observed.
Author Liang Liu
Sarajlic, Muris
Edfors, Ove
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  surname: Liang Liu
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  givenname: Ove
  surname: Edfors
  fullname: Edfors, Ove
  email: ove.edfors@eit.lth.se
  organization: Dept. of Electr. & Inf. Technol., Lund Univ., Lund, Sweden
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Snippet This paper presents a structured optimization framework for reducing the computational complexity of LDPC decoders. Subject to specified performance...
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SubjectTerms Algorithm design and analysis
Complexity theory
Convergence
Decoding
Iterative decoding
Signal to noise ratio
Title Reducing the complexity of LDPC decoding algorithms: An optimization-oriented approach
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