Project Outline:
As wireless communications become ubiquitous in our daily life, the emerging illegal use of the radio frequency (e.g., jamming, malicious interference, covert transmission) is causing increasing privacy and security concerns. Against this background, the detection of the malicious signals in the context of wireless networks is of growing importance. In such detection, the radio frequency (RF) noise power plays a critical rule, since noise widely exists in a RF system even when an information signal does not exist. This project is on collecting and modelling the RF noise power. The first task of this project is to conduct a thorough literature review on the available RF noise power dataset and models, understanding the noise theory, methods of measuring RF noise power, and the noise power uncertainty source. The second task of this project is to collect such a dataset via using the available platforms at ECU (e.g., Ettus X310, N210, Spectrum analyzer). Then, the final task is to use the established dataset in one application scenario, such as malicious interference detection, GPS spoofing detection, or covert signal transmission, in which new and novel model should be developed. This project should lead to multiple high-quality journal publications.
Literature samples:
- 10 Counter-Drone Technologies To Detect And Stop Drones Today
- Practical Noise-Figure Measurement and Analysis for Low-Noise Amplifier Designs
- Noise power measurements and measurement uncertainties
Available platforms at ECU:
Preferred Skills (not required): Experience with software define radios, MATLAB, basic wireless communication knowledge.
Project Area: Wireless Cybersecurity
Research Centre: Security Research Institute (SRI)
Supervisor(s): Dr Shihao YAN
Project level: Masters / PhD
Funding: Applicant should apply for ECUHDR or RTP Scholarship
Start date: Any
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