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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Veröffentlicht in:	IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops (Print) S. 861 - 866
Hauptverfasser:	Sarajlic, Muris, Liang Liu, Edfors, Ove
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.09.2014
Schlagworte:	Algorithm design and analysis Complexity theory Convergence Decoding Iterative decoding Signal to noise ratio
ISSN:	2166-9570
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	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.
ISSN:	2166-9570
DOI:	10.1109/PIMRC.2014.7136286