Intelligent Reflecting Surfaces-Supported Terahertz NOMA Communications

In this paper, the sum rate is maximized for the intelligent reflective surface (IRS) assisted terahertz (THz) non-orthogonal multiple access (NOMA) communication system. A novel algorithm is proposed to alternatively optimize the IRS phase shift, the sub-band allocation, and power control. To tackle the formulated non-convex problem, we utilize the auxiliary variables to find the feasible initialization solution meanwhile guarantee the individual rate requirements. The decoding order of successive interference cancellation (SIC) is determined according to channel gain maximization, and the IRS phase is further adjusted to improve the sum rate. A long-distance priority (LDP) algorithm is then proposed to compensate for the distance-dependent THz pathloss attenuation, and a blocking pair eliminating (BPE) algorithm is proposed to obtain a stable THz sub-band allocation. Simulation results show that the proposed scheme significantly enhances the sum-rate performance of the IRS-assisted THz NOMA networks.