@inproceedings{19bedf4beaaf44d18951cbbf61d94b3d,
title = "Power Allocation for Downlink of Non-orthogonal Multiple Access System via Genetic Algorithm",
abstract = "Non-orthogonal multiple access (NOMA) is a promising technology in future communication systems due to high spectral efficiency. In this paper, we propose an efficient power allocation method based on the genetic algorithm (GA) to solve the non-linear optimization problem for maximizing the achievable sum rate under a total power constraint and the users{\textquoteright} quality of service (QoS) in the downlink NOMA systems. Different power allocation coefficients can be obtained with different objective functions and optimization criteria. Simulation results demonstrate that the NOMA systems with power allocation using GA can achieve better performance than the orthogonal multiple access (OMA) systems in terms of the achievable sum rate.",
keywords = "Genetic algorithm, Non-orthogonal multiple access (NOMA), Power allocation, Quality of service (QoS)",
author = "Xinli Ma and Juan Wu and Zhenyu Zhang and Zhongshan Zhang and Xiyuan Wang and Xiaomeng Chai and Linglong Dai and Xiaoming Dai",
note = "Publisher Copyright: {\textcopyright} 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 1st International Conference on 5G for Future Wireless Networks, 5GWN 2017 ; Conference date: 21-04-2017 Through 23-04-2017",
year = "2018",
doi = "10.1007/978-3-319-72823-0_43",
language = "English",
isbn = "9783319728223",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Verlag",
pages = "459--470",
editor = "Zhiyong Feng and Yonghui Li and Leung, {Victor C.M.} and Keping Long and Haijun Zhang and Zhongshan Zhang",
booktitle = "5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings",
address = "Germany",
}