Abstract
This paper investigates unmanned aerial vehicle (UAV) powered multi-user intelligent reflecting surface (IRS) backscatter communication (BackCom). In such a system, an IRS as a passive transmitter sends multiple data streams towards multiple users in a manner of BackCom, while a UAV serves as a mobile power beacon for flexibly supplying radio frequency signals. To maximize the sum rate of all the users, the trajectory of the UAV and its transmit beamforming, as well as the passive beamforming at the IRS, are optimized jointly. Specifically, a block coordinate descent method is firstly leveraged to decompose the original non-convex optimization problem into three tractable subproblems. By developing an alternate iterative algorithm, the transmit beamforming at the UAV, the passive beamforming at the IRS, and the trajectory of the UAV are circularly optimized by employing fractional programming, semidefinite programming, reinforcement learning, etc. The simulation results demonstrate that the proposed joint optimization scheme is feasible in the proposed IRS backscatter communication network.
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