PHY7 – Reconfigurable Intelligent Surfaces
Friday, 5 June 2026, 9:00-10:30, room Sala 1 (1st floor)
Session Chair: Mikko A. Uusitalo (Nokia Bell Labs, FI)
Adaptive Sparse Channel Tracking in RIS-Aided FR3 Networks
Xichun Cheng (Aalto University, Finland); Fabian Göttsch (Technische Universität Berlin, Germany); Risto Wichman and Alexis Alfredo Dowhuszko (Aalto University, Finland); Dennis Osterland and Andreas Benzin (Technische Universitaet Berlin, Germany)
We study the problem of channel tracking in a novel near-field-fed reconfigurable intelligent surface (NFED-RIS) system. In this architecture, the RIS is fed by a small active feeder, and the RIS-feeder link is time-invariant and can be determined via geometric modeling. Consequently, the focus can be shifted to the user equipment (UE)-RIS channel. To efficiently track this channel, we exploit its inherent sparsity in the angular domain and propose the online variational sparse Bayesian filter (OVSBF), an adaptive algorithm for dynamic sparse recovery. Numerical results demonstrate that OVSBF significantly outperforms the existing methods by jointly leveraging both channel sparsity and temporal correlation.
Multi-User Reflection Modulation via Reconfigurable Intelligent Surfaces with Resource Allocation
Pasan Karunasena, Nandana Rajatheva and Matti Latva-aho (University of Oulu, Finland)
Multi-user communication is essential for deploying reconfigurable intelligent surfaces (RIS) successfully in future wireless networks. Reflection modulation (RM) offers an additional paradigm for information transfer, where the RIS passively modulates additional information through activation patterns. Incorporating RM into multi-user downlink communications requires the RIS to convey different additional data to different users simultaneously. Current literature on single-RIS systems primarily focuses on optimizing the RIS reflection coefficients in a common passive beamforming design that collectively serves multiple users. This may be insufficient for RM applications, as well as for spatially distinct users with diverse user requirements. In this paper, we present a framework to adapt RM in multi-user communications, and propose to divide the RIS into user-dedicated subunits to facilitate independent RM data transfer, by introducing two RIS resource allocation methods: equal subunit separation and channel state information (CSI)-based subunit separation. We formulate the jointly active and passive beamforming problem accordingly and modify the existing alternating optimization (AO) and decoupled two-stage optimization algorithms to account for RIS resource allocation. Numerical results confirm that RIS resource allocation methods enhance beamforming performance, with improved convergence and error performance in RM applications.
OSIRIS: A Strategy for Online Codebook-Based RIS Configuration
Alexandros Ioannis Papadopoulos (University of Ioannina, Greece & Information Technologies Institute, Greece); Dimitrios Tyrovolas (Aristotle University of Thessaloniki, Greece & University of Patras, Greece); Antonios Lalas (Centre for Research and Technology – Hellas (CERTH), Greece); Konstantinos Votis (Information Technologies Institute, Centre For Research and Technology Hellas, Greece); George K. Karagiannidis (Aristotle University of Thessaloniki, Greece); Christos Liaskos (University of Ioannina, Greece & Foundation of Research and Technology Hellas, Greece)
Next-generation wireless networks must provide reliable, low-latency connectivity in environments marked by severe multipath and channel variability. Programmable wireless environments address this by enabling deterministic control of wave propagation through software-defined reconfigurable intelligent surfaces (RISs). However, configuring thousands of RIS elements in real time remains a major bottleneck. Therefore, we propose OSIRIS, an optimized strategy for instantiating RIS codebook entries that compresses a small set of physics-accurate, oracle-optimal configurations into a compact codebook. OSIRIS computes optimal phase profiles on a sparse 3D set of anchor locations using a physics-aware EM oracle, clusters these profiles in the phase domain, and uses an anchor-guided search to select codebook entries online. By evaluating only a fixed, small number of candidate clusters, OSIRIS offers deterministic runtime and near-optimal beam focusing without large datasets or retraining. Simulations show that OSIRIS preserves the accuracy of physics-aware optimization while substantially reducing compilation time and supporting practical real-time RIS operation.
Performance Improvements of 5G mmW Network with RIS in Underground Mine Environment
Klaus Nevala, Sohaib Bin Shahid, Mina Tavangar and Duccio Delfini (University of Oulu, Finland); Achilleas Seisa (Lulea University of Technology, Sweden); Antti Pauanne (University of Oulu, Finland); Michael Nilsson and George Nikolakopoulos (Lulea University of Technology, Sweden); Marko E Leinonen (University of Oulu, Finland)
Digitalization of the mining industry requires efficient wireless communication systems to support autonomous vehicles, remote operations and high datarates. The highest datarates in 5G system can be achieved at millimeter wave (mmW) frequencies but those suffer rapid signal strength attenuation around the mine tunnel corners. This paper pioneers standalone 5G mmW network in underground mine environment with a reflective intelligent surface (RIS). The incidence and reflection angles to and from the RIS can be programmed individually. The measurement results show significant improvement of the 5G mmW cell coverage from the main tunnel to the side tunnel from 4 meters up to 22 meters. The signal to interference and noise results followed the received signal power levels indicating that there was no additional mmW frequency interference present during the measurements. The signal level estimation based on radar cross section analysis had very good match with the measurement signal levels.
RIS-Assisted Rank Enhancement with Commodity WiFi Transceivers: Real-World Experiments
Aymen Khaleel (Ruhr Universität Bochum, Germany); Aydin Sezgin (RUB, Germany)
Reconfigurable intelligent surfaces (RISs) are a promising enabling technology for the sixth-generation (6G) of wireless communications. RISs, thanks to their intelligent design, can reshape the wireless channel to provide favorable propagation conditions for information transfer. In this work, we experimentally investigate the potential of RISs to enhance the effective rank of multiple-input multiple-output (MIMO) channels, thereby improving spatial multiplexing capabilities. In our experiment, commodity WiFi transceivers are used, representing a practical MIMO system. In this context, we propose a passive beam-focusing technique to manipulate the propagation channel between each transmit-receive antenna pair and achieve a favorable propagation condition for rank improvement. The proposed algorithm is tested in two different channel scenarios: low and medium ranks. Experimental results show that, when the channel is rank-deficient, the RIS can significantly increase the rank by 112% from its default value without the RIS, providing a rank increment of 1.5. When the rank has a medium value, a maximum of 61% enhancement can be achieved, corresponding to a rank increment of 1. These results provide the first experimental evidence of RIS-driven rank manipulation with off-the-shelf WiFi hardware, offering practical insights into RIS deployment for spatial multiplexing gains.
