Joint Beamforming and Location Optimization for UAV-IRS Enhanced Cell-Free Network

Cell-free network and intelligent reflecting surface (IRS) are considered as promising technologies for future network capacity and coverage improvement. They offer advantages such as low cost, low energy consumption, and meeting the requirements of green communication. However, the fixed location of IRS limits the flexibility of the entire network. To address this issue, we propose a more comprehensive cell-free network that enhances network capacity and signal coverage by utilizing the reflected signals from an airborne IRS. Our objective is to maximize the weighted transmission rate for users by jointly optimizing the base station (BS) beamforming, passive beamforming of the IRS, and the location of the UAV. Owing to the non-convex and intricate nature of the problem, we decompose it into three subproblems, employing the principles of Lagrangian duality, multi-ratio fractional programming, and the successive convex approximation (SCA) technique for resolution. Simulation results demonstrate that the proposed scheme can significantly improve the weighted transmission rate and effectively enhance the network coverage compared to the benchmarks.