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Wireless Networks Physical Layer Security Analysis and Improvement
Eldokmak, Youssef Mohamed Abdelfattah
Eldokmak, Youssef Mohamed Abdelfattah
Date
2022-11
Advisor
Type
Thesis
Degree
Description
A Master of Science thesis in Electrical Engineering by Youssef Mohamed Abdelfattah Eldokmak entitled, “Wireless Networks Physical Layer Security Analysis and Improvement”, submitted in November 2022. Thesis advisor is Dr. Mahmoud H. Ismail and thesis co-advisor is Dr. Mohamed Hassan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
With the recent advancements in computational power, traditional security techniques are being challenged since it is now easier for an eavesdropper to decode messages previously deemed to be practically impossible to decode. That is why physical layer security is becoming an important research field that is gaining much attention among the research community. Studying the physical layer security for a wireless network enables us to find different important secrecy performance metrics such as the average secrecy capacity, the secrecy outage probability and the probability of non-zero secrecy capacity. These different metrics can be used to assess the network properly and to know what data rates could be transmitted to a legitimate receiver without an eavesdropper decoding it. As a consequence, studying secrecy performance over different fading channels and under various case scenarios depending on the application has been extensively addressed in the literature. In addition, as much as secrecy performance analysis is important, developing techniques to improve the secrecy performance is as important in order to ensure reliable and secure data transmission. In this thesis, we focus on analysing the secrecy performance over general fading/shadowing channels that have not yet been studied in the literature. Specifically, we focus on the analysis of two cases of the generalized gamma channels. In the first, the signal to noise ratio follows a composite generalized gamma log-normal distribution and in the second, the channels of the legitimate and eavesdropper receivers follow a correlated generalized gamma distribution. These fading models can be used to represent a wide range of channels that are encountered in many practical applications. We finally address how artificial noise could be used in secrecy performance improvement.