Large Intelligent Surfaces With Channel Estimation Overhead: Achievable Rate and Optimal Configuration

Large intelligent surfaces (LIS) present a promising new technology for enhancing the performance of wireless communication systems. Realizing gains LIS requires accurate channel knowledge, and in practice estimation overhead can be large due to passive nature LIS. Here, we study achievable rate LIS-assisted single-input single-output system, accounting pilot least-squares estimator. We demonstrate that there exists an optimal K * , which maximizes by balancing power offered overhead. analytical approximations based on maximizing upper bound average derive, dependencies statistical system parameters.