TY  - CONF
AU  - EL GAILY, SARA
AU  - Almasaoodi, Mohammed
AU  - Sabaawi , Abdulbasit 
AU  - Imre, Sándor
TI  - Constrained Quantum Genetic Algorithm for Maximizing Energy Efficiency in Downlink Massive MIMO Network for 5G Applications
T2  - European Quantum Technologies Conference (EQTC) 2023
PY  - 2023
SP  - 1
EP  - 2
PG  - 2
UR  - https://m2.mtmt.hu/api/publication/34397944
ID  - 34397944
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Sabaawi , Abdulbasit 
AU  - Almasaoodi, Mohammed
AU  - EL GAILY, SARA
AU  - Imre, Sándor
ED  - IEEE, ,
TI  - Unconstrained Quantum Genetic Algorithm for Massive MIMO System
T2  - 2023 17th International Conference on Telecommunications (ConTEL)
PB  - IEEE
CY  - Piscataway (NJ)
SN  - 9798350302233
PY  - 2023
SP  - 1
EP  - 6
PG  - 6
DO  - 10.1109/ConTEL58387.2023.10198943
UR  - https://m2.mtmt.hu/api/publication/34009620
ID  - 34009620
N1  - Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics, Department of Networked Systems and Services, Budapest, H-1111, Hungary            
            College of Electronics Engineering, Ninevah University, Mosul, Iraq            
            Kerbala University, Kerbala, Iraq            
            Export Date: 1 September 2023
ISSN:1847-9774
AB  - There are plenty of real-world applications that require finding extreme value in an unsorted database. This database can be enormously large, such that there is no available quantum computer or classical supercomputer that can execute the search process. We proposed a new unconstrained quantum genetic algorithm (QGA) in order to increase the probability of finding the global solution and escaping from local minima. This algorithm exploits the features provided by blind quantum computation (BQC), which holds the promise to handle this computation issue by delegating computation to quantum remote devices. Massive multiple-input multiple-output (MIMO) systems are used as a toy example for demonstrating the effectiveness of the developed quantum genetic method.
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Almasaoodi, Mohammed
AU  - Sabaawi , Abdulbasit 
AU  - EL GAILY, SARA
AU  - Imre, Sándor
TI  - Optimizing Energy Efficiency of MIMO Using Quantum Genetic Algorithm
T2  - Advances in Science and Engineering Technology International Conferences (ASET2023)
PB  - IEEE
CY  - [s.l.]
SN  - 9781665454742
PY  - 2023
SP  - 1
EP  - 6
PG  - 6
DO  - 10.1109/ASET56582.2023.10180620
UR  - https://m2.mtmt.hu/api/publication/33999708
ID  - 33999708
N1  - Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics, Department of Networked Systems and Services, Budapest, Hungary            
            Kerbala University, Kerbala, Iraq            
            College of Electronics Engineering, Ninevah University, Mosul, Iraq            
            Export Date: 21 August 2023
LA  - English
DB  - MTMT
ER  -