CSI Acquisition for Aerial IRS Supported Cell-Free Communication Systems

In this paper, we consider a cell-free massive multiple input multiple output (CF-MMIMO) communication system, where users are supported by access points (AP) in conjunction with intelligent reflecting surfaces (IRS) mounted on unmanned aerial vehicles (UAVs). Although aerial IRS (aIRS) offers agile support for expanding network coverage in CF communication systems, the effective operation of such a complex network necessitates a channel state information (CSI) acquisition scheme that exhibits low run-time computational complexity. We propose an artificial intelligence (AI)-based approach to design and develop an efficient channel prediction scheme for CSI acquisition in the CF-MMIMO network supported by aIRS considered. Simulation results demonstrate the effectiveness of the proposed scheme in predicting channel gains across a wide range of signal-to-noise ratios (SNR) while maintaining low computational complexity during real-time operations.