Intelligent Reflecting Surface Enhanced Multi-UAV NOMA Networks

Intelligent reflecting surface (IRS) enhanced multi-unmanned aerial vehicle (UAV) non-orthogonal multiple access (NOMA) networks are investigated. A new transmission framework is proposed, where UAV-mounted base stations employ NOMA to serve groups of ground users with the aid an IRS. The three-dimensional (3D) placement and transmit power UAVs, reflection matrix IRS, decoding orders among jointly optimized for maximization sum rate considered networks. To tackle formulated mixed-integer non-convex optimization problem coupled variables, a block coordinate descent (BCD)-based iterative algorithm developed. Specifically, original decomposed into three subproblems, which alternatingly solved by exploiting penalty method successive convex approximation technique. proposed BCD-based demonstrated be able obtain stationary point polynomial time complexity. Numerical results show that: 1) NOMA-IRS scheme multi-UAV achieves higher compared benchmark schemes, i.e., orthogonal (OMA)-IRS without IRS; 2) use IRS capable providing performance gain both enhancing channel qualities UAVs their served mitigating inter-UAV interference; 3) optimizing UAV can make brought more distinct due flexible order design.