Channel Estimation for RIS-Aided Communication Systems: A Task-Based Quantization Approach

We investigate a cascaded channel estimation approach for reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user multiple-input single-output communication systems. To mitigate the high cost and power consumption of analog-to-digital converters (ADCs) in mmWave base stations with many antennas and wide signal bandwidths, we propose a task-based quantization approach using identical low-resolution scalar ADCs that minimizes the channel estimation error for hybrid analog and digital architectures. Numerical results verify that the performance of the proposed channel estimation design can effectively approach that of a system operating with unlimited resolution ADCs, and outperform a system operating solely in the digital domain under identical bit-resolution constraints.