On the Hardness of Approximating Stopping and Trapping Sets in LDPC Codes

We prove that approximating the size of the smallest trapping set in Tanner graphs of linear block codes, and more restrictively, LDPC codes, is NP-hard. The proof techniques rely on reductions from three NP-hard problems, the set cover, minimum three-dimensional matching, and the minimum Hamming distance problem. The ramifications of our findings are that methods used for estimating the height of the error-floor of long LDPC codes, centered around trapping set enumeration, cannot provide accurate worst-case performance predictions.