论文标题
用Orbgrand块涡轮增压解码
Block turbo decoding with ORBGRAND
论文作者
论文摘要
猜测随机的添加噪声解码（GRAND）是一个通用解码算法的家族，适用于解码任何长度的任何中等冗余代码。我们确定，通过使用列表解码，Grand的软输入变体可以替代Chase算法作为产品代码涡轮解码中的组件解码器。除了能够解码任意产品代码，而不仅仅是具有专用硬输入组件代码解码器的产品代码外，结果还表明，Orbgrand在列表大小相同的Chase算法上实现了高达0.7db的编码增益。
Guessing Random Additive Noise Decoding (GRAND) is a family of universal decoding algorithms suitable for decoding any moderate redundancy code of any length. We establish that, through the use of list decoding, soft-input variants of GRAND can replace the Chase algorithm as the component decoder in the turbo decoding of product codes. In addition to being able to decode arbitrary product codes, rather than just those with dedicated hard-input component code decoders, results show that ORBGRAND achieves a coding gain of up to 0.7dB over the Chase algorithm with same list size.
