Combining Blind Equalization and Automatic Modulation Classification in a Loop Structure

Senhao Gao, Mehul Motani

Abstract: The process of demodulating an unknown wireless communication signal without knowledge of the channel state and modulation type is called the dual-blind demodulation problem. We focus on solving the dual-blind demodulation problem in the presence of multipath fading and noise. Traditional blind receivers have different functional blocks to preprocess the incoming signal and recognize the modulation type. However, the independence among these blocks may limit performance. In this paper, we propose a dual-mode equalizer combined with a modulation classifier with a loop evaluation structure, called the automatic modulation classification (AMC) loop. We also introduce an AMC algorithm with a novel cluster-to-constellation (c2c) distance. Via experiments, we show that the proposed loop structure achieves better demodulation and classification accu-racy in a dual-blind scenario than (i) the traditional approach without the loop structure, and (ii) loop structures with alternate AMC algorithms. We also show that the proposed novel AMC-Loop structure with an AMC based on c2c distance is crucial for good performance via an ablation study.