Robust Tensor-Based Algorithm for UAV-Assisted IoT Communication Systems via Nested PARAFAC Analysis

In this paper, we propose a robust tensor-based strategy to jointly estimate channel state information (CSI) and detect information symbols for unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) communication systems. First, a superimposed signal transmission scheme is designed for each IoT device, and the superimposed signals are transmitted to UAVs simultaneously. Then, UAVs amplify and forward the received signals to the base station (BS), where a combined nested parallel factor (PARAFAC) tensor model is constructed. Finally, a robust tensor-based algorithm is derived to estimate full knowledge of CSI and detect information symbols. Simulation results show that the proposed algorithm offers superior performance compared with the competitive methods.