论文标题
雷利褪色频道的盛大
GRAND for Rayleigh Fading Channels
论文作者
论文摘要
猜测随机的添加噪声解码（GRAND）是一种用于短长度和高速通道代码的代码不合时宜的解码技术。 Grand试图通过产生测试误差模式（TEP）来猜测通道噪声，而TEP的序列是不同大变体之间的主要区别。在这项工作中，我们将Grand的应用扩展到多路径频率非选择性的雷利褪色通信渠道，我们将此大变种称为褪色的狂热。拟议的褪色习惯将其TEP生成适应了基本通信渠道的褪色条件，在具有$ L $空间多样性分支的场景中，在场景中表现优于传统的频道代码解码器，而没有多样性。数值模拟结果表明，淡出的戒指优于传统的Berlekamp-Massey（B-M）解码器，用于解码BCH代码$（127,106）$（127,106）$（127,113）$（127,113）$（127,113）$（127,113）$（$ \ MATHBF {0.5 \ sim6.5} $ db的目标均为$ 10^^$ 10^{-7}。同样，淡出的格兰德（Grand）胜过Grandab，Grand的硬输入变化，$ 0.2 \ sim8 $ db，目标fer $ 10^{ - 7} $，带有CRC $（128,104）$ CODE和RLC $（128,104）$。此外，褪色习惯的平均复杂性为$ \ frac {e_b} {n_0} $对应于$ 10^{ - 7} $的目标fer，为$ \ frac {1} {1} {2} \ times \ times \ sim \ sim \ sim \ sim \ sim \ frac {1} {1} {46} {46} {46} {46} {46} \ times $ times $ spers $ spers $
Guessing Random Additive Noise Decoding (GRAND) is a code-agnostic decoding technique for short-length and high-rate channel codes. GRAND tries to guess the channel noise by generating test error patterns (TEPs), and the sequence of the TEPs is the main difference between different GRAND variants. In this work, we extend the application of GRAND to multipath frequency non-selective Rayleigh fading communication channels, and we refer to this GRAND variant as Fading-GRAND. The proposed Fading-GRAND adapts its TEP generation to the fading conditions of the underlying communication channel, outperforming traditional channel code decoders in scenarios with $L$ spatial diversity branches as well as scenarios with no diversity. Numerical simulation results show that the Fading-GRAND outperforms the traditional Berlekamp-Massey (B-M) decoder for decoding BCH code $(127,106)$ and BCH code $(127,113)$ by $\mathbf{0.5\sim6.5}$ dB at a target FER of $10^{-7}$. Similarly, Fading-GRAND outperforms GRANDAB, the hard-input variation of GRAND, by $0.2\sim8$ dB at a target FER of $10^{-7}$ with CRC $(128,104)$ code and RLC $(128,104)$. Furthermore the average complexity of Fading-GRAND, at $\frac{E_b}{N_0}$ corresponding to target FER of $10^{-7}$, is $\frac{1}{2}\times\sim \frac{1}{46}\times$ the complexity of GRANDAB.
