Robust and Outage-Constrained Energy Efficiency Optimization in RIS-Assisted NOMA Networks

Robustness and energy efficiency (EE) are of crucial importance in reconfigurable intelligent surface (RIS)-assisted wireless communication networks. However, a large portion of the current works assume that perfect channel state information (CSI) can be obtained, which is impractical because of the passive features of the RIS and the lack of radio frequency chains at the RIS. To handle this issue, we investigate an alternating optimization (AO) algorithm in an RIS-assisted non-orthogonal multiple-access (NOMA) network with imperfect CSI. The EE-based maximization resource allocation problem is formed with the maximum transmit power constraint at the base station, the continuous phase shifts constraint of the RIS, and the outage probability constraint of the signal-to-interference-noise ratio. To solve the tricky non-convex fractional problem, Dinkelbach's method is used to convert the fractional objective function into parameter subtraction form, and the S-procedure is utilized to deal with the non-convex outage probability constraint with channel uncertainties. Moreover, by applying the AO algorithm the original optimization problem is converted into several semi-definite programming (SDP) subproblems. The overall simulation results illustrate that the proposed algorithm has good robustness and EE.