Broadcasting systems often suffer from coverage limitation and uneven service quality, particularly in non-line-of- sight (NLOS) environments. Reconfigurable intelligent surface (RIS) has emerged as a promising technology capable of reshaping electromagnetic propagation paths to enhance signal coverage in complex wireless environments. However, the inability for RIS to directly acquire channel state information (CSI) restricts its adaptability. In this paper, we propose a novel hybrid RIS (HRIS)-assisted broadcasting scheme that maximizes the minimum signal-to-noise ratio (SNR) of users, where HRIS enables simultaneous signal reflection and real-time CSI acquisition. We formulate the problem as the maximization of the worst-case SNR of users by optimizing the HRIS phase configuration based on directly acquired CSI. A gradient-based optimization algorithm is developed to iteratively update the phase matrix of HRIS while preserving the fairness among users in broadcasting system. Simulation results demonstrate that the proposed scheme achieves considerable improvements in SNR and sum rate of all users. Moreover, a prototype system is implemented with an 8×8 HRIS array. The measurement results show good consistency with the simulation results. The experimental validation further confirms the effectiveness of the proposed scheme, achieving up to 16.47 dB performance enhancement.

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for enhancing communication systems. This paper investigates a novel flexible-position RIS-assisted communication system, where the RIS is mounted on a slide rail, enabling spatial adaptability. Unlike traditional fixed-position RISs, the proposed system leverages both spatial flexibility and phase reconfigurability to optimize system performance while reducing overhead through strategic position adjustment. To characterize the spatial variations introduced by RIS movement, we propose a generalized RIS channel model that integrates a practical visibility region function with near-field spherical wave propagation. This model captures the spatial correlation characteristics influenced by multipath angular spread, scatterer distribution, and RIS positioning. Furthermore, we introduce a measurement scheme using a multi-state RIS hardware to analyze segmented channels across fixed-position and flexible-position scenarios. Our measurement reveals that the intra-cluster power angular spectrum follows a Gaussian distribution, and in strong scattering environments, spatial correlation exhibits an enhanced degree of freedom due to spatial non-stationarity effects. In particular, the experimental results demonstrate that the gain of the received power varies from 0.4 dB to 5.3 dB across different RIS positions, providing empirical evidence that spatial adaptability of RIS effectively resists channel non-stationarity. These findings highlight the potential of flexible-position RIS to enhance future wireless communication systems.

With the capability to configure wireless propagation environment, reconfigurable intelligent surface (RIS) has attracted wide attention from both academia and industry, in which measurement campaign of RIS in commercial networks is of great importance for performance evaluation. However, existing RIS configuration schemes in practical environments are generally angle-based which require accurate angle information and mainly consider single incident beam, or statistical methods with high sampling overhead. In this paper, we propose a phase shift design scheme for RIS referred to as multiple incident beam superposition (MIBS) scheme, which can be applied in scenarios with incident signals on the RIS from multiple directions. Instead of utilizing random sampling, the proposed scheme firstly employs an incident beam scanning process to extract the incident beam information by pre-calculated codebook to reduce sampling cost, and requires no complex channel estimation or prior channel information. Then the proposed scheme concentrates the incident beams toward the desired reflection direction through a phase shift superposition algorithm. Numerical simulations verify the excellent performance and a 90% sample reduction of the proposed scheme compared with existing methods under the condition of 1-bit RIS hardware for practical applications. Furthermore, a measurement campaign in 5G commercial networks is conducted to validate the advantages of the proposed MIBS scheme in optimizing crucial signal metrics, yielding a 6.76 dB RSRP gain, a 4.9 dB SINR gain and a 37% throughput improvement, showing great potential of RIS for coverage enhancement.

Reconfigurable intelligent surfaces (RISs) offer new possibilities for manipulating wireless propagation environments. However, existing studies on RIS-assisted multiple-input multiple-output (MIMO) channel modeling are limited in their ability to explicitly separate and reveal the RIS-induced effects within the cascaded channel. This paper investigates the modeling and measurement of RIS-assisted MIMO channels from a spatial decomposition perspective. We propose a novel stochastic channel modeling framework based on the Weichselberger model, which decomposes the channel into a controllable RIS-induced component and an uncontrollable scattering component. This formulation reveals the RIS’s capability to reshape the spatial coupling structure of MIMO channels and enables the analysis of eigenmode control through spatial correlation and phase configuration. To experimentally validate the model, we develop a channel measurement and separation scheme using a multi-state RIS that can switch among reflective, absorptive, and antenna states. This setup allows for direct extraction of RIS channel component and supports segmented channel measurements. Measurement results show that the RIS-induced and environmental scattering components exhibit distinct power angular spectra and coupling matrices, and their superposition accurately reconstructs the global channel behavior. Additionally, the measured RIS coupling matrix closely matches the one calculated by the theoretical model, with a correlation matrix distance of 0.0394. These results confirm the effectiveness of the proposed model and measurement strategy, offering new insights into RIS-enabled spatial channel customization for next-generation wireless systems.

Reconfigurable intelligent surface (RIS) has garnered significant attention in wireless communications due to its electromagnetic wave manipulation capabilities. In order to ensure the effectiveness of various transmission designs in practical environment, the channel characteristics of RIS-assisted wireless communication systems warrant thorough investigation. While substantial research has been conducted on large-scale channel characteristics, there remains a lack of measurement-based studies on channel small-scale characteristics. This paper conducts channel measurement campaigns, analyzing delay characteristics and multi-cluster properties in multiple indoor and outdoor environments, including square, corridor, and classroom scenarios. The measurement results indicate that the RIS-assisted path (i.e. the virtual line-of-sight (VLOS) path) makes the channels exhibit two-cluster characteristics analogous to conventional line-of-sight channels. Moreover, in classroom scenario, VLOS path generates reflected echoes that degrade the channel delay characteristics. Building on these findings, this paper proposes a small-scale channel modeling framework comprising a two-cluster-based channel impulse response (CIR) model and a K-factor-based CIR model. The simulation and measurement results demonstrate satisfactory agreement, validating the effectiveness and practicality of the proposed framework. Two types of CIR models that are unified with the traditional CIR model form, along with an optional echo component, make this framework flexible and easy to use. The proposed small-scale modeling framework can effectively characterize the power delay profiles of RIS-assisted channels, providing References for future research on RIS-assisted wireless communications.

Reconfigurable intelligent surfaces (RISs) are widely recognized as a cutting-edge technology for the sixth-generation mobile communication systems (6G). In this paper, we investigate the effective channel gain and spatial multiplexing gain of multi-RIS-assisted millimeter wave (mmWave) multiple-input multiple-output (MIMO) channels. A channel model for multi-RIS-assisted MIMO system is introduced. We propose two discrete phase design methods for multi-RIS-assisted MIMO systems. The factors influencing spatial multiplexing gain, including the power difference and spatial similarity between different virtual line-of-sight (VLOS) paths, are thoroughly analyzed. Numerical simulations and measurement experiments are conducted in three scenarios, analyzing the impact of the RIS unit number as well as the positions of the RISs and antennas. The results indicate that jointly considering the position information of multiple RISs in discrete phase design leads to a higher effective channel gain, whereas relying only on the position of each single RIS exhibits instability. These findings highlight the positive role of sufficient location information and joint phase design in multi-RIS-assisted systems. Moreover, the results demonstrate that reduced power difference and spatial similarity among VLOS paths enhance the effective rank of the cascaded mmWave MIMO channel.

Reconfigurable intelligent surface (RIS) has gained significant attention as an innovative solution for enhancing communication system performance. This paper proposes a novel fluid RIS-assisted communication system with spatial adaptability, where the RIS is mounted on a slide rail. By leveraging both spatial flexibility and phase reconfigurability, the proposed system overcomes the limitations of conventional fixed-position RIS. To characterize the spatial variations introduced by RIS movement, we establish a novel channel modeling framework that combines near-field spherical wave propagation with practical visibility region functions. Experimental results reveal that dynamic RIS position yields received power gain variations ranging from 0.4 dB to 5.3 dB. This empirical evidence strongly validates the capability of fluid RIS to counteract channel non-stationarity.

The deployment of multiple reconfigurable intelligent surfaces (RISs) enhances the propagation environment by improving channel quality, but it also complicates channel estimation. Following the conventional wireless communication system design, which involves full channel state information (CSI) acquisition followed by RIS configuration, can reduce transmission efficiency due to substantial pilot overhead and computational complexity. This study introduces an innovative approach that integrates CSI acquisition and RIS configuration, leveraging the channel-altering capabilities of the RIS to reduce both the overhead and complexity of CSI acquisition. The focus is on multi-RIS-assisted systems, featuring both direct and reflected propagation paths. By applying a fast-varying reflection sequence during RIS configuration for channel training, the complex problem of channel estimation is decomposed into simpler, independent tasks. These fast-varying reflections effectively isolate transmit signals from different paths, streamlining the CSI acquisition process for both uplink and downlink communications with reduced complexity. In uplink scenarios, a positioning-based algorithm derives partial CSI, informing the adjustment of RIS parameters to create a sparse reflection channel, enabling precise reconstruction of the uplink channel. Downlink communication benefits from this strategically tailored reflection channel, allowing effective CSI acquisition with fewer pilot signals. Simulation results highlight the proposed methodology’s ability to accurately reconstruct the reflection channel with minimal impact on the normalized mean square error while simultaneously enhancing spectral efficiency.

Reconfigurable intelligent surfaces (RISs) offer the unique capability to reshape the radio environment, thereby simplifying transmission schemes traditionally contingent on channel conditions. Joint spatial division and multiplexing (JSDM) emerges as a low-overhead transmission scheme for multi-user equipment (UE) scenarios, typically requiring complex matrix decomposition to achieve block-diagonalization of the effective channel matrix. In this study, we introduce an innovative JSDM design that leverages RISs to customize channels, thereby streamlining the overall procedures. By strategically positioning RISs at the discrete Fourier transform (DFT) directions of the base station (BS), we establish orthogonal line-of-sight links within the BS-RIS channel, enabling a straightforward pre-beamforming design. Based on UE grouping, we devise reflected beams of the RIS with optimized directions to mitigate inter-group interference in the RISs-UEs channel. An approximation of the channel cross-correlation coefficient is derived and serves as a foundation for the RISs-UEs association, further diminishing inter-group interference. Numerical results substantiate the efficacy of our RIS-customized JSDM in not only achieving effective channel block-diagonalization but also in significantly enhancing the sum spectral efficiency for multi-UE transmissions.

Reconfigurable intelligent surfaces (RISs) have received extensive concern to improve the performance of wireless communication systems. In this paper, a subarray-based scheme is investigated in terms of its effects on ergodic spectral efficiency (SE) and energy efficiency (EE) in RIS-assisted systems. In this scheme, the adjacent elements divided into a subarray are controlled by one signal and share the same reflection coefficient. An upper bound of ergodic SE is derived and an optimal phase shift design is proposed for the subarray-based RIS. Based on the upper bound and optimal design, we obtain the maximum of the upper bound. In particular, we analytically evaluate the effect of the subarray-based RIS on EE since it reduces SE and power consumption simultaneously. Numerical results verify the tightness of the upper bound, demonstrate the effectiveness of the optimal phase shift design for the subarray-based RIS, and reveal the effects of the subarray-based scheme on SE and EE.

The performance of transmission schemes is heavily influenced by the wireless channel, which is typically considered an uncontrollable factor. However, the introduction of reconfigurable intelligent surfaces (RISs) to wireless communications enables the customization of a preferred channel for adopted transmissions by reshaping electromagnetic waves. In this study, we propose multi-timescale channel customization for RIS-assisted multiple-input multiple-output systems to facilitate transmission design. Specifically, we customize a high-rank channel for spatial multiplexing (SM) transmission and a highly correlated rank-1 channel for beamforming (BF) transmission by designing the phase shifters of the RIS with statistical channel state information in the angle-coherent time to improve spectral efficiency (SE). We derive closed-form expressions for the approximation and upper bound of the ergodic SE and compare them to investigate the relative SE performance of SM and BF transmissions. In terms of reliability enhancement, we customize a fast-changing channel in the symbol timescale to achieve more diversity gain for SM and BF transmissions. Extensive numerical results demonstrate that flexible customization of channel characteristics for a specific transmission scheme can achieve a tradeoff between SE and bit error ratio performance.

In strong line-of-sight millimeter-wave (mmWave) wireless systems, the rank-deficient channel severely hampers spatial multiplexing. To address this inherent deficiency, multiple reconfigurable-intelligent-surfaces (RISs) are introduced in this study to customize the wireless channel. Utilizing the RIS to reshape electromagnetic waves, we theoretically show that a favorable channel with an arbitrary tunable rank and a minimized truncated condition number can be established by elaborately designing the placement and reflection matrix of RISs. Different from existing works on multi-RISs, the number of elements needed for each RIS to combat the path loss and the limited phase control is also considered. On the basis of the proposed channel customization, a joint transmitter-RISs-receiver (Tx-RISs-Rx) design under a hybrid mmWave system is investigated to maximize the spectral efficiency. Using the proposed scheme, the optimal singular value decomposition-based hybrid beamforming at the Tx and Rx can be obtained without matrix decomposition for the digital and analog beamforming. The bottoms of the sub-channel mode in the water-filling algorithm, which are conventionally uncontrollable, are proven to be independently adjustable by RISs. Moreover, the transmit power required for realizing multi-stream transmission is derived. Numerical results are presented to verify our theoretical analysis and exhibit substantial gains over systems without RISs.

Reconfigurable intelligent surfaces (RISs) represent a pioneering technology to realize smart electromagnetic environments by reshaping the wireless channel. Jointly designing the transceiver and RIS relies on the channel state information (CSI), whose feedback has not been investigated in multi-RIS-assisted frequency division duplexing systems. In this study, the limited feedback of the RIS-assisted wireless channel is examined by capitalizing on the ability of the RIS in channel customization. By configuring the phase shifters of the surfaces using statistical CSI, we customize a sparse channel in rich-scattering environments, which significantly reduces the feedback overhead in designing the transceiver and RISs. Since the channel is customized in terms of singular value decomposition (SVD) with full-rank, the optimal SVD transceiver can be approached without a matrix decomposition and feeding back the complete channel parameters. The theoretical spectral efficiency (SE) loss of the proposed transceiver and RIS design is derived by considering the limited CSI quantization. To minimize the SE loss, a bit partitioning algorithm that splits the limited number of bits to quantize the CSI is developed. Extensive numerical results show that the channel customization-based transceiver with reduced CSI can achieve satisfactory performance compared with the optimal transceiver with full CSI. Given the limited number of feedback bits, the bit partitioning algorithm can minimize the SE loss by adaptively allocating bits to quantize the channel parameters.

To address the inherent channel deficiency in strong line-of-sight (LoS) millimeter-wave (mmWave) wireless systems, distributed reconfigurable intelligent surfaces (RISs) are introduced in this study to customize the wireless channel. Capitalizing on the ability of the RIS to reshape electromagnetic waves, we theoretically show that a favorable channel with an arbitrary tunable rank and a minimized truncated condition number can be established by elaborately designing the placement and reflection matrix of RISs. The number of elements needed for each RIS to combat the path loss is also considered in this research. Numerical results show that the effective channel rank can be flexibly and accurately customized according to the required number of data streams. Moreover, utilizing our proposal, every corner in the interested coverage can build the well-conditioned channel with small truncated condition number.

In frequency division duplexing systems, the base station (BS) acquires downlink channel state information (CSI) via channel feedback, which has not been adequately investigated in the presence of RIS. In this study, we examine the limited channel feedback scheme by proposing a novel cascaded codebook and an adaptive bit partitioning strategy. The RIS segments the channel between the BS and mobile station into two sub-channels, each with line-of-sight (LoS) and non-LoS (NLoS) paths. To quantize the path gains, the cascaded codebook is proposed to be synthesized by two sub-codebooks whose codeword is cascaded by LoS and NLoS components. This enables the proposed cascaded codebook to cater the different distributions of LoS and NLoS path gains by flexibly using different feedback bits to design the codeword structure. On the basis of the proposed cascaded codebook, we derive an upper bound on ergodic rate loss with maximum ratio transmission and show that the rate loss can be cut down by optimizing the feedback bit allocation during codebook generation. To minimize the upper bound, we propose a bit partitioning strategy that is adaptive to diverse environment and system parameters. Extensive simulations are presented to show the superiority and robustness of the cascaded codebook and the efficiency of the adaptive bit partitioning scheme.

Multiband operation in millimeter wave (mmWave) will obtain lots of performance gain by offering larger bandwidth. However, the prerequisite is the acquisition of accurate channel state information (CSI), which is a knotty task with hybrid analog/digital architecture. This study devotes to efficiently reconstruct and track the time drifting multiband channel to keep CSI precise in time division duplex (TDD) mmWave multiple-input-multiple-output system with hybrid analog/digital architecture. Utilizing spatial reciprocity, an efficient multiband channel reconstruction scheme is introduced, which elaborately estimates the central sub-band channel and then reconstructs side sub-band channels from the central one. To this end, a beam training-based Newtonized orthogonal matching pursuit (BT-NOMP) algorithm is proposed to estimate the central sub-band channel. With the help of frequency-independent parameters extracted from BT-NOMP, side sub-bands channel can be well reconstructed with additional low-complexity path gains estimation process. Furthermore, to avoid frequent channel reconstruction in a slightly drifting channel meanwhile keep the CSI accurate, a rotated beam-based channel tracking algorithm is developed using historical observations of channel parameters. Numerical results prove the efficiency of the proposed multiband channel reconstruction scheme and the accuracy of the channel tracking algorithm.

Recently, reconfigurable intelligent surfaces (RISs) have drawn intensive attention to enhance the coverage of millimeter wave (mmWave) communication systems. However, existing works mainly consider the RIS as a whole uniform plane, which may be unrealistic to be installed on the facade of buildings when the RIS is extreme large. To address this problem, in this paper, we propose a sparse array of sub-surface (SAoS) architecture for RIS, which contains several rectangle shaped sub-surfaces termed as RIS tiles that can be sparsely deployed. An approximated ergodic spectral efficiency of the SAoS aided system is derived and the performance impact of the SAoS design is evaluated. Based on the approximated ergodic spectral efficiency, we obtain an optimal reflection coefficient design for each RIS tile. Analytical results show that the received signal-to-noise ratios can grow quadratically and linearly to the number of RIS elements under strong and weak LoS scenarios, respectively. Furthermore, we consider the visible region (VR) phenomenon in the SAoS aided mmWave system and find that the optimal distance between RIS tiles is supposed to yield a total SAoS VR nearly covering the whole blind coverage area. The numerical results verify the tightness of the approximated ergodic spectral efficiency and demonstrate the great system performance.