  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.
