Active STAR-RIS-Assisted Cell-Free Massive MIMO With Low-Resolution ADCs

This paper studies the simultaneous transmitting and reflecting reconfigurable intelligent surfaces (Active STAR-RIS) assisted cell-free massive MIMO multiple-input multiple-output system with a low-resolution analog-to-digital converter (ADC). An additive quantization noise model (AQNM) is investigated to capture the effect of the low-resolution ADC. Closed-form expressions for linear minimum mean square error channel estimation is derived. Furthermore, we derive the uplink spectral efficiency (SE) in closed form under maximum ratio combined receiver filter. Based on this analytical framework, we undertake a quantitative exploration of how various system parameters influence the uplink SE. Moreover, a detailed trade-off analysis is conducted to evaluate the deployment of supplementary access points (APs) in comparison to the integration of additional RISs. In order to enhance the precision of channel estimation, this paper develops a normalized mean square error optimization framework that minimizes errors across all UEs. This approach simultaneously reduces the pilot transmit power and mitigates pilot contamination during the uplink pilot training phase, utilizing a successive convex approximation method.