To meet the Ultra Reliable Low Latency Communication (URLLC) needs of modern applications, there have been significant advances in the development of short error correction codes and corresponding soft detection decoders. A substantial hindrance to delivering low-latency is, however, the reliance on interleaving to break up omnipresent channel correlations to ensure that decoder input matches decoder assumptions. Consequently, even when using short codes, the need to wait to interleave data at the sender and de-interleave at the receiver results in significant latency that acts contrary to the goals of URLLC. Moreover, interleaving reduces channel capacity, so that potential decoding performance is degraded. Here we introduce a variant of Ordered Reliability Bits Guessing Random Additive Noise Decoding (ORBGRAND), which we call ORBGRAND-Approximate Independence (ORBGRAND-AI), a soft-detection decoder that can decode any moderate redundancy code and overcomes the limitation of existing decoding paradigms by leveraging channel correlations and circumventing the need for interleaving. By leveraging correlation, not only is latency reduced, but error correction performance can be enhanced by multiple dB, while decoding complexity is also reduced, offering one potential solution for the provision of URLLC.

翻译：为满足现代应用对超可靠低延迟通信（URLLC）的需求，短纠错码及其相应软检测解码器的研发取得了显著进展。然而，实现低延迟的一个主要障碍在于依赖交织技术来打破普遍存在的信道相关性，以确保解码器输入与其假设相匹配。因此，即使使用短码，在发送端等待数据交织、在接收端等待数据解交织的过程会导致显著延迟，这与URLLC的目标相悖。此外，交织会降低信道容量，从而削弱潜在的解码性能。本文提出有序可靠比特猜测随机加性噪声解码（ORBGRAND）的一种变体——近似独立ORBGRAND（ORBGRAND-AI），这是一种软检测解码器，能解码任意中等冗余码，并通过利用信道相关性、规避交织需求，克服了现有解码范式的局限性。通过利用相关性，不仅降低了延迟，还将纠错性能提升了数分贝，同时降低了解码复杂度，为提供URLLC提供了一种潜在解决方案。