Frame-Error-Rate-wise Optimal Code-Aided Hypothesis Testing

This paper addresses the issue of code-aided hypothesis testing in communication systems, i.e., the estimation of discrete-valued nuisance parameters. A hypothesis testing procedure optimal in the sense of the minimization of the frame-error rate (FER) is derived. Its complexity is shown to be comparable to other recently-proposed code-aided hypothesis procedures. Moreover, when a conditional maximum a posteriori decision rule is used to make the decisions about the transmitted sequence, it is shown that the proposed hypothesis testing procedure combined with sequence detection reduces, in a good approximation, to a joint maximum-likelihood problem. Finally, as an illustrative example, we show the case of phase ambiguity resolution for a convolutionally-coded transmission.