Locally-Optimized Reweighted Belief Propagation for Decoding Finite-Length LDPC codes
Paper in proceeding, 2013

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.

decoding techniques

belief propagation algorithms

LDPC codes

Author

Jingjing Liu

University of York

Rodrigo de Lamare

University of York

Henk Wymeersch

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

IEEE Wireless Communications and Networking Conference, WCNC

15253511 (ISSN)

4311-4316
978-146735939-9 (ISBN)

Cooperative Situational Awareness for Wireless Networks (COOPNET)

European Commission (EC) (EC/FP7/258418), 2011-05-01 -- 2016-04-30.

Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems

DOI

10.1109/WCNC.2013.6555271

ISBN

978-146735939-9

More information

Latest update

8/29/2023