Authors:
Mohammed R. Almasaoodi
1
;
2
;
Abdulbasit M. A. Sabaawi
3
;
1
;
Sara El Gaily
1
and
Sándor Imre
1
Affiliations:
1
Department of Networked Systems and Services, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
;
2
Kerbala University, Kerbala, Iraq
;
3
College of Electronics Engineering, Ninevah University, Mosul, Iraq
Keyword(s):
Quantum Computing, MIMO, Constrained Quantum Optimization Algorithm, Water Filling Algorithm, Exhaustive Algorithm, Binary Searching Algorithm.
Abstract:
Co-channel interference and noise power could affect the performance of the MIMO system and can be evaluated with respect to the user’s signal to noise and interference ratio. As a result, the desired transmission rate of the users could be satisfied by consuming more transmit power. Owing to this, a quantum optimization strategy can be utilized in order to minimize the transmit power, as well as to achieve an optimum trade-off within the throughput and the resulting interference and noise. In this study, a constrained quantum optimization algorithm (CQOA) has been implemented in the MIMO-downlink system to reduce the transmit power and computational complexity. An analytical study is conducted along with a comparison between the water filling algorithm-based binary searching algorithm (WFA-BSA), exhaustive algorithm-based water filling algorithm (EWFA), and the CQOA. Finally, simulation results show that the aforementioned methods consume similar total transmit power, however, the c
omputational complexity of the quantum strategy is dramatically low compared to the other methods.
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