Guessing Random Additive Noise Decoding (GRAND) is a recently proposed universal Maximum Likelihood (ML) decoder for short-length and high-rate linear block-codes. Soft-GRAND (SGRAND) is a prominent soft-input GRAND variant, outperforming the other GRAND variants in decoding performance; nevertheless, SGRAND is not suitable for parallel hardware implementation. Ordered Reliability Bits-GRAND (ORBGRAND) is another soft-input GRAND variant that is suitable for parallel hardware implementation, however it has lower decoding performance than SGRAND. In this paper, we propose List-GRAND (LGRAND), a technique for enhancing the decoding performance of ORBGRAND to match the ML decoding performance of SGRAND. Numerical simulation results show that LGRAND enhances ORBGRAND's decoding performance by $0.5-0.75$ dB for channel-codes of various classes at a target FER of $10^{-7}$. For linear block codes of length $127/128$ and different code-rates, LGRAND's VLSI implementation can achieve an average information throughput of $47.27-51.36$ Gbps. In comparison to ORBGRAND's VLSI implementation, the proposed LGRAND hardware has a $4.84\%$ area overhead.

翻译：随机随机添加添加噪音标记(GRAND)是最近提议的一种通用最大允许值(ML)解码器,用于短期和高容量线性成块码。软GRAND(SGRAND)是一个显著的软投入GRAND变体,优于其他GRAND变体,在解码性能方面优于其他GRAND变体;然而,SGRAND并不适合于平行的硬件执行。有顺序的 Refority Bit-GRAND(ORBGRAND)是另一个适合平行硬件执行的软投入GRAND变体,但比SGRAND的解码性能要低。在本文中,我们提出LOSGRAND(LGAND)的解码性能提高ORBAND(OD)的解码性能技术,在10美元至7美元的指标FER(FER)下,对各等级的频道代码代码代码值值进行修改。在127—128美元和不同的代码区域执行中,LGRAADADA(O)可达到一个平均的域域域域。