Abstract
In this paper, we present an algorithm1 to
decode non-binary LDPC (NB-LDPC) codes, inspired from
very-high throughput symbol-flipping decoders that have
been proposed recently. Usually, the symbol-flipping decoders
suffer from a non-negligible performance degradation compared
to soft-decision NB-LDPC decoders. Our improved
decoder makes use of a list of syndrome computations
instead of a single one, and builds soft information at the
symbol node input by assigning votes with different weights
to the elements of the list. We show by simulations that
using multiple votes results in better performance, while still
maintaining the high throughput feature.
