Abstract

Stopping sets and stopping set distribution of an low-density parity-check code are used to determine the performance of this code under iterative decoding over a binary erasure channel (BEC). Let CC be a binary [n,k][n,k] linear code with parity-check matrix HH, where the rows of HH may be dependent. A stopping set SS of CC with parity-check matrix HH is a subset of column indices of HH such that the restriction of HH to SS does not contain a row of weight one. The stopping set distribution {Ti(H)}i=0n\{T_i(H)\}_{i=0}^n enumerates the number of stopping sets with size ii of CC with parity-check matrix HH. Note that stopping sets and stopping set distribution are related to the parity-check matrix HH of CC. Let H∗H^{*} be the parity-check matrix of CC which is formed by all the non-zero codewords of its dual code C⊥C^{\perp}. A parity-check matrix HH is called BEC-optimal if Ti(H)=Ti(H∗),i=0,1,...,nT_i(H)=T_i(H^*), i=0,1,..., n and HH has the smallest number of rows. On the BEC, iterative decoder of CC with BEC-optimal parity-check matrix is an optimal decoder with much lower decoding complexity than the exhaustive decoder. In this paper, we study stopping sets, stopping set distributions and BEC-optimal parity-check matrices of binary linear codes. Using finite geometry in combinatorics, we obtain BEC-optimal parity-check matrices and then determine the stopping set distributions for the Simplex codes, the Hamming codes, the first order Reed-Muller codes and the extended Hamming codes.

Explore this paper’s authors, topics and related work.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Reviews 0

Write a reviewWrite

No reviews yet.

Discussion 0

Add a commentWrite

No comments yet.