🤖 AI Summary
This study addresses how the likelihood ranking of candidate noise sequences in list decoding influences the posterior probability that the first-ranked entry is correctly decoded. Leveraging Soft-Output Guessing Random Additive Noise Decoding (SOGRAND) and a random codebook model, we construct a finite-blocklength conditional probability framework to analyze how subsequent list entries affect the reliability of the first entry. We prove that the asymptotic reliability of the first entry depends solely on the first, second, and last rankings. Furthermore, we derive the decision functions and exponential rates governing its convergence to either one or zero, revealing a “rescue” effect whereby a late-emerging second-ranked entry can substantially enhance confidence in the first entry.
📝 Abstract
In error correction, the difference between a codeword and a received word, a candidate noise sequence, carries information on the confidence of the codeword as a proposed decoding. For additive channels, it is known that if noise sequences are ranked in decreasing order of likelihood, a lower rank correlates with higher confidence in a decoding. Here we substantially expand considerations by exploring the relationship between the likelihood ranks arising in list decoding and the posterior probability of decoding correctness, establishing that the ranks associated with subsequent list entries carry reliability information that is not obtainable from the first rank alone.
Building on the recent development of Soft-Output Guessing Random Additive Noise Decoding, we first show that, under a random codebook model, soft-output expressions for list decoding coincide with the exact finite-blocklength conditional probabilities of decoding correctness. For hard-decision maximum likelihood decoding, we characterize the asymptotic reliability of the first list entry. We identify a decision function whose sign determines whether the posterior correctness probability of the first entry in the list converges to one or zero and whose absolute value gives the exponential rate of convergence. Perhaps surprisingly, the asymptotic reliability of the first list entry depends only on the first, second and last ranks.
For list size one, the result recovers the previously known likelihood-rank threshold for reliable decoding. For list size two, a sufficiently late second entry can imply that the first entry is asymptotically correct even when its rank, viewed in isolation, would indicate otherwise.