6 papers
QCommE2E: An Open-Source Simulation of End-to-End Quantum Communication Systems
Omar Alnaseri
This paper presents QCommE2E as an open-source simulation framework for end-to-end quantum communication systems, with explicit tutorial emphasis. The primary objective is to devel…
A Review on Quantum Satellite Communications: Challenges and Future Directions
Omar Alnaseri, Yassine Himeur, Ahmed Al Asadi +4
Quantum satellite communication (QSC) is emerging as a strategic technology for secure global networking and long-distance quantum connectivity. This review prioritizes the major c…
A Review on Deep Learning Autoencoder in the Design of Next-Generation Communication Systems
Omar Alnaseri, Laith Alzubaidi, Yassine Himeur +3
Traditional mathematical models used in designing next-generation communication systems often fall short due to inherent simplifications, narrow scope, and computational limitation…
Complexity of Post-Quantum Cryptography in Embedded Systems and Its Optimization Strategies
Omar Alnaseri, Yassine Himeur, Shadi Atalla +1
With the rapid advancements in quantum computing, traditional cryptographic schemes like Rivest-Shamir-Adleman (RSA) and elliptic curve cryptography (ECC) are becoming vulnerable,…
End-to-End Deep Learning in Phase Noisy Coherent Optical Link
Omar Alnaseri, Yassine Himeur
In coherent optical orthogonal frequency-division multiplexing (CO-OFDM) fiber communications, a novel end-to-end learning framework to mitigate Laser Phase Noise (LPN) impairments…
Deep Learning Autoencoders for Reducing PAPR in Coherent Optical Systems
Omar Alnaseri, Ibtesam R. K. Al-Saedi, Yassine Himeur +1
This paper presents an innovative approach to mitigating the peak-to-average power ratio (PAPR). The proposed method uses a deep learning model called autoencoders (AEs) to simplif…