Outage Probability Constrained MIMO-NOMA Designs Under Imperfect CSI

Non-orthogonal multiple access (NOMA) has been recognized as a promising multiple access scheme to be used in fifth-generation wireless networks. In this paper, multiple-input and multiple-output (MIMO) techniques are applied to NOMA systems by considering two types of imperfect channel state information—channel distribution information (CDI) and channel estimation uncertainty. Based on the two considered channel models, the power allocation and beamforming vectors are jointly designed to maximize the system utility of MIMO-NOMA, subjected to probabilistic constraints. Due to the implementation of successive interference cancellation in NOMA, the power allocation coefficients of the users in each cluster become coupled, which complicates the rate outage probability constraints and results in two challenging non-convex problems. For the optimization problem under CDI, we propose an efficient successive convex approximation (SCA) algorithm based on first-order approximation and semidefinite programming (SDP). For the optimization problem under channel estimation uncertainty, a new algorithm for the joint power allocation and receive beamforming design is developed to maximize the system utility based on SCA and an efficient 1-D search. In addition, the convergence and the feasibility are discussed for the two formulated problems. Furthermore, an efficient method to find a feasible initial solution is provided. Finally, the presented simulation results validate that the proposed two algorithms outperform MIMO-orthogonal multiple access and MIMO fixed NOMA (MIMO F-NOMA) with fixed power allocation and beamforming.