Robust Energy Efficiency Resource Allocation Algorithm in Reconfigurable Intelligent Surface-assisted Non-Orthogonal Multiple Access Networks

To improve the robustness and Energy Efficiency (EE) of Non-Orthogonal Multiple Access (NOMA)-based networks, a robust EE maximization-based algorithm is proposed in a Reconfigurable Intelligent Surface(RIS)-assisted NOMA network with imperfect channel state information. Considering the outage probability constraints of users' Signal-to-Interference-to-Noise Ratio (SINR), the maximum transmit power constraints of the base station, and continuous phase shift constraints, a nonlinear EE maximization-based resource allocation model is established. By using Dinkelbach's method the fractional objective function is converted into a linear parameter subtraction form, the S-procedure method is used to transform the outage probability of SINR with channel uncertainty into deterministic form. By using the alternative optimization method, the non-convex optimization problem is converted into several convex optimization subproblems, then the CVX is used to solve the subproblems. Simulation results show that the proposed algorithm is 7.4% higher than the without Reconfigurable Intelligent Surface (RIS) algorithm in terms of EE, the proposed algorithm is 85.5% lower than the non-robust algorithm in terms of the outage probability of SINR.