Research Article
Power Allocation for Downlink of Non-orthogonal Multiple Access System via Genetic Algorithm
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@INPROCEEDINGS{10.1007/978-3-319-72823-0_43, author={Xinli Ma and Juan Wu and Zhenyu Zhang and Zhongshan Zhang and Xiyuan Wang and Xiaomeng Chai and Linglong Dai and Xiaoming Dai}, title={Power Allocation for Downlink of Non-orthogonal Multiple Access System via Genetic Algorithm}, proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings}, proceedings_a={5GWN}, year={2018}, month={1}, keywords={Non-orthogonal multiple access (NOMA) Quality of service (QoS) Power allocation Genetic algorithm}, doi={10.1007/978-3-319-72823-0_43} }- Xinli Ma
Juan Wu
Zhenyu Zhang
Zhongshan Zhang
Xiyuan Wang
Xiaomeng Chai
Linglong Dai
Xiaoming Dai
Year: 2018
Power Allocation for Downlink of Non-orthogonal Multiple Access System via Genetic Algorithm
5GWN
Springer
DOI: 10.1007/978-3-319-72823-0_43
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’ 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.
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