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Directional Modulation Based on a Quantum Genetic Algorithm for a Multiple-Reflection Model

Yuwei Huang1, 2, Xiubo Chen1, 3, *, Kaiguo Yuan1, 3, Jianyi Zhang4, Biao Liu2

1 Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
2 Beijing Electronic Science and Technology Institute, Beijing, 100070, China.
3 Sate Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, China.
4 School of Computing and Informatics, The University of Louisiana at Lafayette, Lafayette, LA 70503, USA.

* Corresponding Author: Xiubo Chen. Email: email.

Computers, Materials & Continua 2020, 64(3), 1771-1783.


Directional modulation is one of the hot topics in data security researches. To fulfill the requirements of communication security in wireless environment with multiple paths, this study takes into account the factors of reflections and antenna radiation pattern for directional modulation. Unlike other previous works, a novel multiple-reflection model, which is more realistic and complex than simplified two-ray reflection models, is proposed based on two reflectors. Another focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna array. The quantum approach has strengths in convergence speed and the globe searching ability for the complicated model with the large-size antenna array and multiple paths. From this, a phased directional modulation transmission system can be optimized as regards communication safety and improve performance based on the constraint of the pattern of the antenna array. Our work can spur applications of the quantum evolutionary algorithm in directional modulation technology, which is also studied.


Cite This Article

Y. Huang, X. Chen, K. Yuan, J. Zhang and B. Liu, "Directional modulation based on a quantum genetic algorithm for a multiple-reflection model," Computers, Materials & Continua, vol. 64, no.3, pp. 1771–1783, 2020.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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