Guo et al. recently presented a reaction attack against the QC-MDPC McEliece cryptosystem. Their attack is based on the observation that when a bit-flipping decoding algorithm is used in the QC-MDPC McEliece, then there exists a dependence between the secret matrix H and the failure probability of the bit-flipping algorithm. This dependence can be exploited to reveal the matrix H which constitu...

Aiming at seeking a low complexity decoder of the low-density parity-check (LDPC) codes, we present one modified multi-bit flipping (MMBF) algorithm. For those LDPC codes whose parity check matrices have light column weight, both the bootstrap step and a novel delay-handling step are included in MMBF, based on one framework which is the combination of conventional PWBF and IWBF. On the other ha...

In this paper we investigate decoding performance of binary low-density codes based on extended Hamming codes, using a hard decision decoding algorithm similar to Gallager’s bit-flipping algorithm. The possibilities to implement the decoder in hardware are also discussed.

SUMMARY We have researched high dimensional parity-check (HDPC) codes that give good performance over a channel that has a very high error rate. HDPC code has a little coding overhead because of its simple structure. It has hard-in, maximum detected bit flipping (MDBF) decoding that has reasonable decoding performance and computational cost. In this paper, we propose a modified algorithm for MD...

This paper presents two techniques for the design of digital filters with wordlength-constrained coefficients, the bit-flipping algorithm improved since it was first presented in [l] and the Downhill Simplex Method [2] modified to deliver fixed-point filter coefficients. Both techniques can be applied to design of filter coefficients from scratch or to the optimisation of their floatingpoint ve...

Low-density parity-check codes are studied over Markov channels with time-varying gaussian or bit-flipping noise. The belief propagation decoding algorithm is extended to include channel estimation and the gains this extension produce are experimentally determined.

A stack of n pancakes can be rearranged in all n! ways by a sequence of n!−1 flips, and a stack of n ‘burnt’ pancakes can be rearranged in all 2nn! ways by a sequence of 2nn!−1 flips. In both cases, a computer program can efficiently generate suitable solutions. We approach these tasks instead from a human perspective. How can we determine the next flip directly from the current stack? How can ...