A probabilistic subspace approach to the minimal stopping set problem

Determining the minimum size of stopping sets of a linear code is an important and yet difficult combinatorial problem for which the exhaustive search requires exponentially growing complexity. We propose a probabilistic subspace approach that can be applied to discover stopping sets of small size in a linear code, particularly for low-density parity-check (LDPC) codes.