Measurement-Based Spatial Characteristic Analysis for RIS-Assisted mmWave MIMO Channels

Reconfigurable intelligent surface (RIS) is regarded as one of the promising technologies for the sixth-generation mobile communication systems (6G) due to its ability to reshape the wireless channel and improve the communication transmission rate. In this paper, we investigate the spatial characteristic of an RIS-assisted millimeter wave (mmWave) multiple-input multipleoutput (MIMO) channel through channel measurement in practical environment. The channel measurement campaigns are carried out in an indoor hotspot (InH) non-line-of-sight (NLOS) scenario at 35 GHz. We compare and analyze the channel parameters in three propagation modes, including intelligent reflection with RIS (IRWR), specular reflection with RIS (SRWR), and without RIS (WR). Different types of receiver (RX) antenna are compared, including the horn antenna and the omni-directional antenna. Signals with bandwidths of 300 MHz and 10 MHz are transmitted to compare the spatial characteristics of wideband and narrowband signals. The measured channel frequency response (CFR) reveals that the RIS coding scheme, antenna type, and signal bandwidth are significant factors influencing the spatial correlation of the wireless channel. The measured power azimuth spectrum (PAS), fitted by truncated Laplacian functions, demonstrates that the deployment of RIS with energy-focused phase configuration results in an amplification of the power in the primary signal propagation direction. Moreover, the analysis of the root mean square (RMS) angular spread shows that it increases with the growing distance between the RX and RIS.

Authors

Institutions

Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174563
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Measurement-Based Spatial Characteristic Analysis for RIS-Assisted mmWave MIMO Channels

Wankai Tang, Boning Gao, Li Xiao, Jian Sang et al.
Advanced MIMO Systems Optimization
article

Measurement-Based Spatial Characteristic Analysis for RIS-Assisted mmWave MIMO Channels

Wankai Tang, Boning Gao, Li Xiao, Jian Sang, Ziang Wang, Shi Jin, Chenhong Yang, Haiming Wang
article en

Abstract

Reconfigurable intelligent surface (RIS) is regarded as one of the promising technologies for the sixth-generation mobile communication systems (6G) due to its ability to reshape the wireless channel and improve the communication transmission rate. In this paper, we investigate the spatial characteristic of an RIS-assisted millimeter wave (mmWave) multiple-input multipleoutput (MIMO) channel through channel measurement in practical environment. The channel measurement campaigns are carried out in an indoor hotspot (InH) non-line-of-sight (NLOS) scenario at 35 GHz. We compare and analyze the channel parameters in three propagation modes, including intelligent reflection with RIS (IRWR), specular reflection with RIS (SRWR), and without RIS (WR). Different types of receiver (RX) antenna are compared, including the horn antenna and the omni-directional antenna. Signals with bandwidths of 300 MHz and 10 MHz are transmitted to compare the spatial characteristics of wideband and narrowband signals. The measured channel frequency response (CFR) reveals that the RIS coding scheme, antenna type, and signal bandwidth are significant factors influencing the spatial correlation of the wireless channel. The measured power azimuth spectrum (PAS), fitted by truncated Laplacian functions, demonstrates that the deployment of RIS with energy-focused phase configuration results in an amplification of the power in the primary signal propagation direction. Moreover, the analysis of the root mean square (RMS) angular spread shows that it increases with the growing distance between the RX and RIS.

State Key Laboratory of Millimeter Waves, Southeast University (CN)
Openalex Percentile: Top 73%
Advanced MIMO Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.