  Decoding via sequentially guessing the error pattern in a received noisy
sequence has received attention recently, and ORBGRAND has been proposed as one
such decoding algorithm that is capable of utilizing the soft information
embedded in the received noisy sequence. An information theoretic study is
conducted for ORBGRAND, and it is shown that the achievable rate of ORBGRAND
using independent and identically distributed random codebooks almost coincides
with the channel capacity, for an additive white Gaussian noise channel under
antipodal input. For finite-length codes, improved guessing schemes motivated
by the information theoretic study are proposed that attain lower error rates
than ORBGRAND, especially in the high signal-to-noise ratio regime.
