Hybrid Near/Far-Field Communications of RIS-Aided Cell-Free Massive MIMO With Visibility Region Detection

Abstract

This paper analyzes visibility region (VR) detection and spectral efficiency (SE) in a reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) system, with a focus on hybrid near-field (NF) and far-field (FF) communication. A statistical channel model is introduced, leveraging the Fresnel approximation and Rayleigh distance concepts. To enable VR detection using signals received from the radio-frequency (RF) chains of the RIS, a novel detection matrix based on the Welch-bound-equality (WBE) codebook is proposed. Its performance is thoroughly analyzed, with closed-form expressions derived for the probabilities of missed detection and false alarm. Based on the estimated VRs, a generalized expression for the estimated aggregated channel from the user equipment (UE) to the access point (AP) is derived using the linear minimum mean-squared-error (LMMSE) estimator, which supports SE analysis. To mitigate pilot contamination during VR detection and channel state information (CSI) estimation, a novel two-stage pilot assignment scheme is proposed. In the VR detection stage, orthogonal pilots are assigned to NF-UEs while FF-UEs remain silent, enhancing detection accuracy. In the CSI estimation stage, UE-AP cooperation is integrated with pilot assignment and power control, delivering superior SE performance compared to the group-based scheme.