A Derivation of the Asymptotic Random-Coding Prefactor
Jonathan Scarlett, Alfonso Martinez, Albert Guill\'en i, F\`abregas
TL;DR
This paper refines Gallager's techniques to derive the asymptotic random-coding prefactor, extending recent results to mismatched decoding scenarios, providing deeper insights into the subexponential behavior of coding bounds.
Contribution
It offers an alternative proof of the asymptotic random-coding prefactor and extends the analysis to mismatched decoding settings.
Findings
Refined Gallager's bounding techniques for asymptotic analysis
Extended the random-coding prefactor result to mismatched decoding
Provided a new proof of a recent theoretical result
Abstract
This paper studies the subexponential prefactor to the random-coding bound for a given rate. Using a refinement of Gallager's bounding techniques, an alternative proof of a recent result by Altu\u{g} and Wagner is given, and the result is extended to the setting of mismatched decoding.
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Taxonomy
TopicsWireless Communication Security Techniques · Cellular Automata and Applications · DNA and Biological Computing