… Adachi, “Lightweight automatic modulation classification based on decentralized learning,” …
for automatic modulation classification,” IEEE Communications Letters, vol. 26, no. 8, pp. …

… from experts in the field of automatic modulation classification. O’shea et al. [43] first introduced
CNN into the field of automatic modulation classification and proposed an AMC method …

… Automatic modulation classification (AMC) is a vital process … is fundamentally a classification
problem. It is employed to … for modulation classification, utilizing the residual learning and …

… an increasing scarcity of spectrum resources for the internet of vehicles (IoV), which has
given rise to an urgent requirement for automatic modulation classification (AMC) in cognitive …

… ary decentralized Bayesian hypothesis testing problem is given by a system of nonlinear
coupled equations. It is shown in [83] that even the simplest problems of decentralized decision …

… As a decentralized ML method, the FL has brought the … for automatic modulation recognition
over Rayleigh fading … Zhang, “Automatic modulation classification based on novel feature …

… Automatic modulation classification (AMC) is a useful technology for Internet of Things …
automatically distinguish the modulation scheme of the received signal. Recently, deep learning …

… Automatic Modulation Classification (AMC), a vital component for classifying and dynamically
adjusting modulation … central model while maintaining decentralized processing. However, …

… In this paper, we have presented RepCCNet, a novel deeplearning framework for automatic
modulation classification. Our core innovations include re-parameterizable causal con…

… learning (DL) models for automatic modulation classification (… limits their ability to
classify higher-order modulation formats. To … The decentralized learningbased AMC (DecentAMC) …