Time-Domain Channel Measurements and Small-Scale Fading Characterization for RIS-Assisted Wireless Communication Systems

TL;DR

This work presents a time-domain RIS channel measurement framework based on USRP hardware to quantify small-scale fading in RIS-assisted channels. It analyzes PDPs and multipath parameters across corridor and lab environments for three modes: without RIS, RIS specular, and RIS intelligent reflection, revealing that intelligent reflection concentrates energy on a VLoS path and lowers delay spread. The study adopts a STDL PDP model with 5 ns bins and 300 taps, and utilizes power-law PDP decay with $p_k = a/\tau_k^{n_{PDP}}$ to fit RIS-enabled channels better than exponential decay, complemented by Saleh–Valenzuela clustering with an improved bubbling algorithm to characterize cluster dynamics. The findings show environment-dependent clustering and fading reductions, highlighting the practical impact of RIS intelligent reflection on channel quality, coverage, and design of RIS-assisted systems.

Abstract

Reconfigurable intelligent surfaces (RISs) have attracted extensive attention from industry and academia. In RIS-assisted wireless communication systems, practical channel measurements and modeling serve as the foundation for system design, network optimization, and performance evaluation. In this paper, a RIS time-domain channel measurement system, based on a software defined radio platform, is developed for the first time to investigate the small-scale fading characteristics of RIS-assisted channels. We present RIS channel measurements in corridor and laboratory scenarios and compare the power delay profile of the channel without RIS, with RIS specular reflection, and with RIS intelligent reflection. The multipath component parameters and cluster parameters based on the Saleh-Valenzuela model are extracted. We find that the power delay profiles (PDPs) of the RIS-assisted channel fit the power-law decay model better than the common exponential decay model and approximate the law of square decay. Through intelligent reflection, the RIS can decrease the delay and concentrate the energy of the virtual line-of-sight (VLoS) path, thereby reducing the delay spread and mitigating multipath fading. Furthermore, the cluster characteristics of RIS-assisted channels are highly dependent on the measurement environment. In the laboratory scenario, a single cluster dominated by the VLoS path with smooth envelope is observed. On the other hand, in the corridor scenario, some additional clusters introduced by the RIS reflection are created.

Figures (14)

• Figure 1: The architecture diagram of the USRP-based RIS time-domain channel measurement system, where the main hardware equipment, the USRP internal data stream and the synchronization module of the system are illustrated.
• Figure 2: The physical diagram of the used RIS and its unit cell.
• Figure 3: The schematic diagram of the RIS sub-channel for intelligent reflection.
• Figure 4: The channel measurement campaign carried out in the corridor scenario: (a) Schematic diagram of the measurement environment with measurement points marked with blue dots, where "r$m$" denotes the $m$-th row and "c$n$" denotes the $n$-th column. (b) Diagram of the real measurement scene.
• Figure 5: The channel measurement campaigns carried out in the laboratory scenario: (a) Schematic diagram of the measurement environment with the measurement points marked with "R(number)". (b) Diagram of the real measurement scene.