دورية أكاديمية
Signals Intelligence System with Software-Defined Radio
| العنوان: | Signals Intelligence System with Software-Defined Radio |
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| المؤلفون: | Florin Radu, Petru A. Cotfas, Marian Alexandru, Titus C. Bălan, Vlad Popescu, Daniel T. Cotfas |
| المصدر: | Applied Sciences, Vol 13, Iss 8, p 5199 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| مصطلحات موضوعية: | software-defined radio, artificial intelligence, Azure, signal modulation, modulation detection, GNU Radio, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| الوصف: | In this paper, we present the implementation of a system that identifies the modulation of complex radio signals. This is realized using an artificial intelligence model developed, trained, and integrated with Microsoft Azure cloud. We consider that cloud-based platforms offer enough flexibility and processing power to use them instead of conventional computers for signal processing based on artificial intelligence. We tested the implementation using a software-defined radio platform developed in GNU Radio that generates and receives real modulated signals. This process ensures that the solution proposed is viable to be used in real signal processing systems. The results obtained show that for certain modulation types, the identification is performed with a high degree of success. The use of a cloud-based platform allows quick access to the system. The user is able to identify the signal modulation using only a laptop that has access to the internet. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2076-3417 |
| العلاقة: | https://www.mdpi.com/2076-3417/13/8/5199Test; https://doaj.org/toc/2076-3417Test |
| DOI: | 10.3390/app13085199 |
| الوصول الحر: | https://doaj.org/article/c06dade8b4b54fb0b278923439d79698Test |
| رقم الانضمام: | edsdoj.06dade8b4b54fb0b278923439d79698 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20763417 |
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| DOI: | 10.3390/app13085199 |