Abstract
In this paper, we consider automatic modulation classification (AMC) from received signals over flat fading channels. AMC is a technique to identify the modulation type of the transmitted symbols by using received symbols. First, we develop a method to determine the modulation type based on the Neyman-Pearson (NP) detector. Then, to reduce the numerical complexity, a method by using probability density function (PDF) approximation is derived. To certify our detector can be scarcely effected by the uncertainty in noise variance, we compare the case that the noise variance is available with the case that the noise variance is unavailable. Furthermore numerical simulations are conducted to assess the performance of our proposed methods even when only finite samples are limited.
