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Concentration of Random-Coding Error Exponents

Accepted version
Peer-reviewed

Type

Conference Object

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
Sponsorship
European Research Council (725411)