Poster: Cloud Computing with AI-empowered Trends in Software-Defined Radios: Challenges and Opportunities

被引:1
|
作者
Sharma, Ekta [1 ]
Deo, Ravinesh C. [1 ]
Davey, Christopher P. [1 ]
Carter, Brad D. [2 ]
Salcedo-Sanz, Sancho [3 ]
机构
[1] Univ Southern Queensland, Sch Math Phys & Comp, Springfield, Qld 4300, Australia
[2] Univ Southern Queensland, Ctr Astrophys, Toowoomba, Qld 4350, Australia
[3] Univ Alcala, Dept Signal Proc & Commun, Alcala De Henares 28805, Spain
关键词
cloud computing; artificial intelligence; software-defined radio; modulation; GNU Radio; signal classification; ARTIFICIAL-INTELLIGENCE;
D O I
10.1109/WoWMoM60985.2024.00054
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Artificial Intelligence (AI) and Software Defined Radio (SDR) are transforming the field of signal intelligence. However, the full extent of the capabilities is unknown. This poster presents a paper in development that introduces a cloud-based platform leveraging artificial intelligence to detect and apply 11 modulation schemes (8 digital and 3 analog) to complex or quadrature radio signals. The SNR values analysed range from 0.0 to 40.0, with moderate drift, slight fading, and labelled increments. A comprehensive synthetic database developed by DeepSig is used to train four AI models. These will be integrated with the Google Cloud AI platform to enhance flexibility and processing power. The system will undergo testing with an SDR platform in GNU Radio, showcasing its potential for real-world signal processing applications. Cloud-based platforms offer the adaptability and computational power needed to replace traditional computers for AI-driven signal processing. Initial results indicate successful identification and accurate modulation type detection, with convenient access to the system through internet-connected devices.
引用
收藏
页码:298 / 300
页数:3
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