Reconfigurable intelligent surfaces (RISs) can establish favorable wireless environments to combat the severe attenuation and blockages in millimeter-wave (mmWave) bands. However, to achieve the optimal enhancement of performance, the instantaneous channel state information (CSI) needs to be estimated at the cost of a large overhead that scales with the number of RIS elements and the number of users. In this paper, we design a quasi-static broad coverage at the RIS with the reduced overhead based on the statistical CSI. We propose a design framework to synthesize the power pattern reflected by the RIS that meets the customized requirements of broad coverage. For the communication of broadcast channels, we generalize the broad coverage of the single transmit stream to the scenario of multiple streams. Moreover, we employ the quasi-static broad coverage for a multiuser orthogonal frequency division multiplexing access (OFDMA) system, and derive the analytical expression of the downlink rate, which is proved to increase logarithmically with the power gain reflected by the RIS. By taking into account the overhead of channel estimation, the proposed quasi-static broad coverage even outperforms the design method that optimizes the RIS phases using the instantaneous CSI. Numerical simulations are conducted to verify these observations.

Coarse quantization by using low-resolution analog-to-digital converters (ADCs) is an attractive approach to relieve the burden of power consumption and hardware cost of implementing massive multiple-input multiple-output (MIMO) systems. In this article, we analyze the uplink spectral efficiency of a multiuser massive MIMO system with low-resolution ADCs in the context of orthogonal frequency division multiplexing (OFDM) under multipath channels. Firstly, we develop an efficient pilot scheme which results in a constant average power of the quantization noise for different channel delay power spectrums and also minimizes the mean squared error of channel estimation. Then a tight approximation of the uplink achievable rate is derived in a closed form considering both perfect channel state information (CSI) and estimated CSI. Then we analyze the impact of multipath channels on the system performance. Under perfect CSI, we discover that an increment of multipath taps has a positive impact on compensating the performance degradation due to the quantization noise. Under imperfect CSI, the most beneficial channel is uniformly distributed over a specific number of taps. Simulations are conducted to verify our analytical results.