Expurgated Bounds for the Asymmetric Broadcast Channel

This paper contains two main contributions concerning the expurgation of hierarchical ensembles for the asymmetric broadcast channel. The first is an analysis of the optimal maximum likelihood (ML) decoders for the weak and strong user. Two different methods of code expurgation will be used, that will provide two competing error exponents. The second is the derivation of expurgated exponents under the generalized stochastic likelihood decoder (GLD). We prove that the expurgated exponents achieved for the hierarchical ensemble under GLD decoding are at least as good as the maximum between the random coding error exponents derived in an earlier work by Averbuch and Merhav (2018) and one of our ML–based expurgated exponents.

[1]  Neri Merhav Exact Random Coding Error Exponents of Optimal Bin Index Decoding , 2014, IEEE Transactions on Information Theory.

[2]  Achilleas Anastasopoulos,et al.  Error Exponent for Multiple Access Channels: Upper Bounds , 2015, IEEE Transactions on Information Theory.

[3]  Li Peng,et al.  Expurgated Random-Coding Ensembles: Exponents, Refinements, and Connections , 2013, IEEE Transactions on Information Theory.

[4]  Albert Guillén i Fàbregas,et al.  The likelihood decoder: Error exponents and mismatch , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[5]  Neri Merhav,et al.  Exact Random Coding Exponents and Universal Decoders for the Asymmetric Broadcast Channel , 2018, IEEE Transactions on Information Theory.

[6]  Neri Merhav,et al.  The generalized stochastic likelihood decoder: Random coding and expurgated bounds , 2015, 2016 IEEE International Symposium on Information Theory (ISIT).

[7]  János Körner,et al.  Universally attainable error exponents for broadcast channels with degraded message sets , 1980, IEEE Trans. Inf. Theory.

[8]  Patrick P. Bergmans,et al.  Random coding theorem for broadcast channels with degraded components , 1973, IEEE Trans. Inf. Theory.

[9]  Imre Csiszár,et al.  Graph decomposition: A new key to coding theorems , 1981, IEEE Trans. Inf. Theory.

[10]  János Körner,et al.  General broadcast channels with degraded message sets , 1977, IEEE Trans. Inf. Theory.

[11]  D. A. Bell,et al.  Information Theory and Reliable Communication , 1969 .

[12]  A. Sridharan Broadcast Channels , 2022 .

[13]  Neri Merhav,et al.  Statistical Physics and Information Theory , 2010, Found. Trends Commun. Inf. Theory.

[14]  Neri Merhav,et al.  Error Exponents for Broadcast Channels With Degraded Message Sets , 2011, IEEE Transactions on Information Theory.

[15]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .

[16]  Neri Merhav Correction to “The Generalized Stochastic Likelihood Decoder: Random Coding and Expurgated Bounds” , 2017, IEEE Transactions on Information Theory.

[17]  Neri Merhav,et al.  List Decoding—Random Coding Exponents and Expurgated Exponents , 2013, IEEE Transactions on Information Theory.

[18]  Achilleas Anastasopoulos,et al.  Error Exponent Regions for Gaussian Broadcast and Multiple-Access Channels , 2008, IEEE Transactions on Information Theory.