Error Exponents of Optimum Decoding for the Interference Channel

TL;DR

This paper derives exponential error bounds for the interference channel with two pairs under optimum decoding, showing it outperforms suboptimal decoding methods and involves advanced analytical techniques from statistical physics.

Contribution

It provides the first single-letter expression for error exponents of the interference channel with optimum decoding, improving upon previous suboptimal decoding bounds.

Findings

Optimum decoding yields better error exponents than suboptimal methods.

A single-letter formula for error exponents is derived.

Analytical tools from statistical physics are employed.

Abstract

Exponential error bounds for the finite-alphabet interference channel (IFC) with two transmitter-receiver pairs, are investigated under the random coding regime. Our focus is on optimum decoding, as opposed to heuristic decoding rules that have been used in previous works, like joint typicality decoding, decoding based on interference cancellation, and decoding that considers the interference as additional noise. Indeed, the fact that the actual interfering signal is a codeword and not an i.i.d. noise process complicates the application of conventional techniques to the performance analysis of the optimum decoder. Using analytical tools rooted in statistical physics, we derive a single letter expression for error exponents achievable under optimum decoding and demonstrate strict improvement over error exponents obtainable using suboptimal decoding rules, but which are amenable to more conventional analysis.