Transmit Power Minimization for IRS-Assisted NOMA-UAV Networks

The flexibility of unmanned aerial vehicles(UAVs) allows them to be quickly deployed to support ground users. Intelligent reflecting surface(IRS) can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction. Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS. According to their distance to the UAV, the users are divided into the close users and remote users. The UAV hovers above the close users due to their higher rate requirement, while the IRS is deployed near the remote users to enhance their received power. We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement. However, the problem is non-convex.Therefore, we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization, which are transformed into second-order cone programming and semidefinite programming, respectively. We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.