Mismatched Exponents for Deterministic and Randomised Noise-Guessing Decoding (opens in new tab)

We study both the deterministic and randomised variants of noise-guessing decoding in additive memoryless channels. The error and complexity exponents of such decoding schemes are analysed under mismatched decoding metrics, and then specialised to matched, $\alpha$-tilted, and universal decoding metrics. The $\alpha$-tilted metric is proportional to the $\alpha$-th power ($\alpha>0$) of the true noise distribution. In deterministic decoding, the...