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Improving LDPC Decoders via Informed Dynamic Scheduling

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3 Author(s)
Vila Casado, A.I. ; Univ. of California, Los Angeles ; Griot, M. ; Wesel, R.D.

Low-Density Parity-Check (LDPC) codes are usually decoded by running an iterative belief-propagation (BP), or message-passing, algorithm over the factor graph of the code. The message-passing schedule of the BP algorithm significantly affects the performance of the LDPC decoder. The authors recently presented a novel message-passing schedule, called Informed Dynamic Scheduling (IDS), that selects the message-passing schedule according to the observed rate of change of the messages. IDS yields a lower error-rate performance than traditional message-passing schedules (such as flooding and LBP) because it solves traditional trapping-set errors. However, for short-blocklength LDPC codes, IDS algorithms present non-trapping-set errors in the error floor region. This paper presents a careful analysis of those errors and proposes mixed scheduling strategies, combining LBP with IDS, that solve these non-trapping-set errors. Also, we will show that some lower-complexity techniques, such as mixed scheduling, perform close to the best IDS strategies for larger-blocklength codes.

Published in:

Information Theory Workshop, 2007. ITW '07. IEEE

Date of Conference:

2-6 Sept. 2007