Adaptive Pilot Interval Optimization for Intelligent Reflecting Surface-Aided Communication Systems

Channel estimation plays a crucial role in intelligent reflecting surface (IRS)-aided communication systems, in which the channel state information must be acquired to configure the optimal IRS reflection coefficient. However, using large numbers of IRS elements induce large channel estimation overheads, which cause crucial problems in systems utilizing IRSs. In this study, we investigate the optimal pilot interval design for IRS-aided communication systems to reduce the channel estimation overheads. The channel coherent time depends on user equipment (UE) velocity. Therefore, the proposed method aims to find a pilot interval that balances accuracy of the IRS reflection coefficient with system throughput by considering UE velocity. In the proposed method, we identify the relationship between the mobility of the UE and complex spatial correlation of the channel matrix, and the transmission capacity in a time slot is formulated to maximize the achievable sum rate. Numerical results from simulations show that the proposed method adaptively adjusts the pilot interval under various communication environments.