  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.
