ArticleSensors (Basel, Switzerland)2022
Automatic Modulation Recognition Based on the Optimized Linear Combination of Higher-Order Cumulants.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Artificial intelligence in bread making: Applications in quality control, formulation and sensory prediction.Food chemistry: X · 2026Review
- MFCA-Transformer: Modulation Signal Recognition Based on Multidimensional Feature Fusion.Sensors (Basel, Switzerland) · 2025Article
- Automatic modulation classification for interrupted sampling proximity detector signals using time-frequency reconstruction network and polynomial chirplet transform.Scientific reports · 2025Article
- Optimized Classification of Intelligent Reflecting Surface (IRS)-Enabled GEO Satellite Signals.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
8 authors.
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Abstract
Automatic modulation recognition (AMR) is used in various domains-from general-purpose communication to many military applications-thanks to the growing popularity of the Internet of Things (IoT) and related communication technologies. In this research article, we propose an innovative idea of combining the classical mathematical technique of computing linear combinations (LCs) of cumulants with a genetic algorithm (GA) to create super-cumulants. These super-cumulants are further used to classify five digital modulation schemes on fading channels using the K-nearest neighbor (KNN). Our proposed classifier significantly improves the percentage recognition accuracy at lower SNRs when using smaller sample sizes. A comparison with existing techniques manifests the supremacy of our proposed classifier.
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