Universal Decoding for Gaussian Intersymbol Interference Channels

TL;DR

This paper introduces a universal decoding method for Gaussian ISI channels that is independent of channel parameters and achieves the same error performance as the optimal ML decoder, with an easily evaluable metric.

Contribution

It proposes a frequency domain universal decoder for Gaussian ISI channels that matches ML error exponents without needing channel parameter knowledge.

Findings

Achieves ML error exponent universally

Easily evaluated decoding metric

Independent of channel parameters

Abstract

A universal decoding procedure is proposed for the intersymbol interference (ISI) Gaussian channels. The universality of the proposed decoder is in the sense of being independent of the various channel parameters, and at the same time, attaining the same random coding error exponent as the optimal maximum-likelihood (ML) decoder, which utilizes full knowledge of these unknown parameters. The proposed decoding rule can be regarded as a frequency domain version of the universal maximum mutual information (MMI) decoder. Contrary to previously suggested universal decoders for ISI channels, our proposed decoding metric can easily be evaluated.