Error correction techniques traditionally focus on the co-design of restricted code-structures in tandem with code-specific decoders that are computationally efficient when decoding long codes in hardware. Modern applications are, however, driving demand for ultra-reliable low-latency communications (URLLC), rekindling interest in the performance of shorter, higher-rate error correcting codes, and raising the possibility of revisiting universal, code-agnostic decoders. To that end, here we introduce a soft-detection variant of Guessing Random Additive Noise Decoding (GRAND) called Ordered Reliability Bits GRAND that can accurately decode any moderate redundancy block-code. It is designed with efficient circuit implementation in mind, and determines accurate decodings while retaining the original hard detection GRAND algorithm's suitability for a highly parallelized implementation in hardware. ORBGRAND is shown to provide excellent soft decision block error performance for codes of distinct classes (BCH, CA-Polar and RLC) with modest complexity, while providing better block error rate performance than CA-SCL, a state of the art soft detection CA-Polar decoder. ORBGRAND offers the possibility of an accurate, energy efficient soft detection decoder suitable for delivering URLLC in a single hardware realization.

中文翻译：

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有序可靠性位猜测随机加性噪声解码


纠错技术传统上侧重于受限代码结构与特定于代码的解码器的协同设计，这些解码器在硬件中解码长代码时计算效率高。然而，现代应用正在推动对超​​可靠低延迟通信 (URLLC) 的需求，重新燃起人们对更短、更高速率纠错码性能的兴趣，并提高了重新审视通用、与代码无关的解码器的可能性。为此，我们在这里引入了一种猜测随机加性噪声解码 (GRAND) 的软检测变体，称为有序可靠性位 GRAND，它可以准确解码任何中等冗余的块码。它在设计时考虑了高效的电路实现，并确定准确的解码，同时保留原始硬检测 GRAND 算法对硬件中高度并行化实现的适用性。 ORBGRAND 能够以适度的复杂度为不同类别（BCH、CA-Polar 和 RLC）的代码提供出色的软判决块误码性能，同时提供比 CA-SCL（一种最先进的软检测 CA-SCL）更好的块误码率性能。极性解码器。 ORBGRAND 提供了一种准确、节能的软检测解码器，适合在单一硬件实现中提供 URLLC。