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Edge-Efficient Deep Learning Models for Automatic Modulation Classification: A Performance Analysis
April 25, 2024, 7:42 p.m. | Nayan Moni Baishya, B. R. Manoj, Prabin K. Bora
cs.LG updates on arXiv.org arxiv.org
Abstract: The recent advancement in deep learning (DL) for automatic modulation classification (AMC) of wireless signals has encouraged numerous possible applications on resource-constrained edge devices. However, developing optimized DL models suitable for edge applications of wireless communications is yet to be studied in depth. In this work, we perform a thorough investigation of optimized convolutional neural networks (CNNs) developed for AMC using the three most commonly used model optimization techniques: a) pruning, b) quantization, and c) …
abstract advancement analysis applications arxiv classification communications cs.it cs.lg deep learning devices edge edge devices eess.sp however math.it performance performance analysis stat.ml type wireless wireless communications
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