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Locally-Optimized Reweighted Belief Propagation for Decoding Finite-Length LDPC codes

Jingjing Liu ; Rodrigo de Lamare ; Henk Wymeersch (Institutionen för signaler och system, Kommunikationssystem)
2013 IEEE Wireless Communications and Networking Conference, WCNC 2013; Shanghai; China; 7 April 2013 through 10 April 2013 (1525-3511). p. 4311-4316. (2013)
[Konferensbidrag, refereegranskat]

In practice, LDPC codes are decoded using message passing methods. These methods offer good performance but tend to converge slowly and sometimes fail to converge and to decode the desired codewords correctly. Recently, tree-reweighted message passing methods have been modified to improve the convergence speed at little or no additional complexity cost. This paper extends this line of work and proposes a new class of locally optimized reweighting strategies, which are suitable for both regular and irregular LDPC codes. The proposed decoding algorithm first splits the factor graph into subgraphs and subsequently performs a local optimization of reweighting parameters. Simulations show that the proposed decoding algorithm significantly outperforms the standard message passing and existing reweighting techniques.

Nyckelord: belief propagation algorithms; decoding techniques; LDPC codes



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Denna post skapades 2013-12-15. Senast ändrad 2016-07-12.
CPL Pubid: 189204

 

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Denna publikation är ett resultat av följande projekt:


Cooperative Situational Awareness for Wireless Networks (COOPNET) (EC/FP7/258418)