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This paper is about deriving lower bounds on the error exponents for thetwo-user interference channel under the random coding regime for severalensembles. 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 isin contrast to other, suboptimal decoding rules that have been used in theliterature (e.g., joint typicality decoding, treating interference as noise,etc.). The fact that the interfering signal is a codeword, rather than ani.i.d. noise process, complicates the application of conventional techniques ofperformance analysis of the optimum decoder. Also, unfortunately, theseconventional techniques result in loose bounds. Using analytical tools rootedin statistical physics, as well as advanced union bounds, we derivesingle-letter formulas for the random coding error exponents. We compare ourresults with the best known lower bound on the error exponent, and show thatour 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 theerror exponent associated with the celebrated Han-Kobayashi (HK) random codingensemble, which is based on superposition coding.

Random Coding Error Exponents for the Two-User Interference Channel