Research Article
Power Allocation for NOMA System via Dual Sub-gradient Descent
@INPROCEEDINGS{10.1007/978-3-319-72823-0_50, author={Juan Wu and Xinli Ma and Zhenyu Zhang and Zhongshan Zhang and Xiyuan Wang and Xiaomeng Chai and Linglong Dai and Xiaoming Dai}, title={Power Allocation for NOMA System via Dual Sub-gradient Descent}, 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 Power allocation Log-convex Dual sub-gradient descent}, doi={10.1007/978-3-319-72823-0_50} }- Juan Wu
Xinli Ma
Zhenyu Zhang
Zhongshan Zhang
Xiyuan Wang
Xiaomeng Chai
Linglong Dai
Xiaoming Dai
Year: 2018
Power Allocation for NOMA System via Dual Sub-gradient Descent
5GWN
Springer
DOI: 10.1007/978-3-319-72823-0_50
Abstract
Non-orthogonal multiple access (NOMA) has attracted great attention as a promising downlink multiple access technique for the next generation cellular networks (5G) due to its superior spectral efficiency. Power allocation of multi-user scenario in NOMA is a challenging issue and most of existing works focus on two-user scenario. In this work, we develop a dual sub-gradient descent algorithm based on Lagrange dual function to optimize multi-user power allocation for the multiple-input single-output (MISO) downlink NOMA system. The objective function is a non-convex optimization problem and we can solve it with a log-convex method and an approximation based approach. Numerical results demonstrate that the proposing scheme is able to achieve higher capacity performance for a NOMA transmission system compared with the traditional orthogonal multiple access (OMA) with a few iterations.
