Power Allocation for NOMA System via Dual Sub-gradient Descent

• Published in: 5G for Future Wireless Networks pp. 544 - 555
• Main Authors: Wu, Juan, Ma, Xinli, Zhang, Zhenyu, Zhang, Zhongshan, Wang, Xiyuan, Chai, Xiaomeng, Dai, Linglong, Dai, Xiaoming
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 31.12.2017
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: Dual sub-gradient descent; Log-convex; Non-orthogonal multiple access; Power allocation
• ISBN: 3319728229; 9783319728223
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-319-72823-0_50

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.