Aldebes, Reem and Dimyati, Kaharudin and Hanafi, Effariza (2022) Genetic algorithm for optimizing energy efficiency in downlink mmwave NOMA system with imperfect CSI. Symmetry, 14 (11). ISSN 2073-8994, DOI https://doi.org/10.3390/sym14112345.
Full text not available from this repository.Abstract
Nonorthogonal multiple access (NOMA) is considered a promising technique for improving energy efficiency (EE) in beyond-5G wireless systems. In this paper, we investigate the maximization of EE of downlink wireless systems by combining mmWave with NOMA technologies, considering the asymmetric required data rate of user applications. We propose a genetic algorithm (GA) to solve the non-convex energy efficiency problem for an imperfect CSI downlink mmWave NOMA system. The studied mixed-integer optimization problem was converted to an integer optimization problem and solved using a GA, which determines the best clustering members in mmWave NOMA. The required population size of the proposed GA was determined to evaluate its effectiveness for a massive number of users. In addition, the GA's convergence to the optimal solution for light traffic and relatively heavy traffic was also analyzed. Our results illustrate that the solution obtained solution via GA is almost equal to the optimal value and outperforms the conventional orthogonal multiple access, where the EE is improved by more than 75%. Finally, the impact of the estimation error of CSI on the system performance was evaluated at different required SINR scenarios. The results show that EE is degraded in the case of imperfect CSI case but is still close to the optimal solution.
| Item Type: | Article |
|---|---|
| Funders: | Ministry of Higher Education under the Fundamental Research Grant Scheme |
| Uncontrolled Keywords: | energy efficiency; genetic algorithm; imperfect CSI; millimeter wave (mmWave); non-orthogonal multiple access (NOMA) |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Koh Ai Peng |
| Date Deposited: | 22 Oct 2024 06:44 |
| Last Modified: | 22 Oct 2024 06:44 |
| URI: | http://eprints.um.edu.my/id/eprint/46189 |
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