Concentration of Random-Coding Error Exponents
Accepted version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
Truong, LV
Cocco, G
Font-Segura, J
Guillen I Fabregas, A
Abstract
This paper studies the error exponent of i.i.d. randomly generated codes used for transmission over discrete memoryless channels with maximum likelihood decoding. Specifically, this paper shows that the error exponent of a code, defined as the negative normalized logarithm of the probability of error, converges in probability to the typical error exponent. For high rates, the result is a consequence of the fact that the random-coding error exponent and the sphere-packing error exponent coincide. For low rates, instead, the proof of convergence is based on the fact that the union bound accurately characterizes the probability of error.
Description
Keywords
4613 Theory Of Computation, 46 Information and Computing Sciences, 4006 Communications Engineering, 40 Engineering
Journal Title
2021 IEEE Information Theory Workshop, ITW 2021 - Proceedings
Conference Name
2021 IEEE Information Theory Workshop (ITW)
Journal ISSN
Volume Title
00
Publisher
IEEE
Publisher DOI
Rights
Sponsorship
European Research Council (725411)