User Grouping, Precoding Design, and Power Allocation for MIMO-NOMA Systems

In this paper, we study user grouping, precoding design, and power allocation for multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) systems. An optimization problem is formulated to the maximize sum rate under a transmit constraint at base station constraints on users, which are nonconvex combinatorial thus very challenging solve. To tackle problem, carry out in two steps. first step, exploiting machine learning technique, develop an efficient iterative algorithm grouping design. second power-allocation scheme closed form by recasting original into useful tractable convex form. The numerical results demonstrate that proposed joint scheme, including allocation, considerably outperforms existing schemes terms of maximization, increases sum-rate up 8–18%. addition, show larger number antennas or bigger performance gap, cost less computational complexity.