Power Allocation for NOMA System via Dual Sub-gradient Descent

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.