Guessing random additive noise decoding (GRAND) algorithm has emerged as an excellent decoding strategy that can meet both the high reliability and low latency constraints. This paper proposes a successive addition-subtraction algorithm to generate noise error permutations. A noise error patterns generation scheme is presented by embedding the "1" and "0" bursts alternately. Then detailed procedures of the proposed algorithm are presented, and its correctness is also demonstrated through theoretical derivations. The aim of this work is to provide a preliminary paradigm and reference for future research on GRAND algorithm and hardware implementation.

翻译：随机猜想添加噪音解码算法(GRAND)已经成为一种极好的解码策略,既能满足高度可靠性,又能满足低潜值限制。本文建议采用连续的增量减法算法,产生噪音错误变异。通过将“ 1” 和“ 0” 相继嵌入“ 1” 和“ 0” 相继生成噪音错误模式方案。然后,介绍了拟议算法的详细程序,其正确性也通过理论推导得到证明。这项工作的目的是为GRAND算法和硬件实施的未来研究提供一个初步范例和参考。