Random Coding Error Exponents for the Two-User Interference Channel

Wasim Huleihel, Neri Merhav

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


This paper is about deriving lower bounds on the error exponents for the two-user interference channel under the random coding regime for several ensembles. Specifically, we first analyze the standard random coding ensemble, where the codebooks are comprised of independently and identically distributed (i.i.d.) codewords. For this ensemble, we focus on optimum decoding, which is in contrast to other, suboptimal decoding rules that have been used in the literature (e.g., joint typicality decoding, treating interference as noise, and so on). The fact that the interfering signal is a codeword, rather than an i.i.d. noise process, complicates the application of conventional techniques of performance analysis of the optimum decoder. In addition, unfortunately, these conventional techniques result in loose bounds. Using analytical tools rooted in statistical physics, as well as advanced union bounds, we derive single-letter formulas for the random coding error exponents. We compare our results with the best known lower bound on the error exponent, and show that our exponents can be strictly better. Then, in the second part of this paper, we consider more complicated coding ensembles and find a lower bound on the error exponent associated with the celebrated Han-Kobayashi random coding ensemble, which is based on superposition coding.

Original languageEnglish
Article number7748465
Pages (from-to)1019-1042
Number of pages24
JournalIEEE Transactions on Information Theory
Issue number2
StatePublished - Feb 2017
Externally publishedYes


  • Han-Kobayashi scheme
  • Random coding
  • error exponent
  • interference channels
  • multiuser communication
  • optimal decoding
  • statistical physics
  • superposition coding


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