This article presents a novel reconfigurable intelligent surface (RIS)-integrated base station (BS) by deploying an RIS very close to the base station antennas (BAs), within its radiative near-field range. We propose a practical algorithm to maximize the performance of uplink communications with the proposed RIS-integrated BS while maintaining reasonable complexity. Furthermore, we have implemented a testbed to experiment with the proposed RIS-integrated BS-based uplink multiple-input-multiple-output (MIMO) system. The experimental data validates the performance of the proposed RIS-integrated BS-based uplink MIMO system.

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for next-generation wireless communications due to its ability to manipulate electromagnetic (EM) waves. This work introduces a novel RIS direct modulation scheme based on the backscatter communication concept. In this work, the RIS acts as a sole information modulator. Unlike conventional RIS systems that relay incoming data-carrying waves, this work enables RIS to encode its own information into unmodulated waves without requiring any hardware modifications. We propose an adaptive algorithm that maximizes modulation order while meeting the quality of service (QoS) requirements by selecting appropriate constellation points to minimize error probability. The proposed scheme was validated through simulations and experiments using a passive 5.8 GHz RIS prototype. The validations demonstrate consistent performance in both distributed and co-located transmitter-receiver scenarios. These results highlight its feasibility as an alternative approach for RIS-assisted communications and contribute to further exploration of RIS-enabled symbiotic radio (SR) and over-the-air (OTA) modulation systems.

Reconfigurable intelligent surface (RIS) has gained significant momentum as a cost-effective and energy-efficient technology to enable the next generation of mobile communications. In this article, we propose an RIS-integrated base station (BS) by deploying an RIS sufficiently close to the base station antennas (BAs), within its radiative near-field range. In the proposed RIS-integrated BS system, we utilize RIS as a passive array to reconfigure incoming signals from user equipments (UEs) without experiencing substantial path loss. The near-field channel model between the RIS and BAs is analyzed and applied to the RIS beam control model. Furthermore, we develop a practical algorithm to maximize the performance of the proposed RIS-integrated BS-based uplink multiple-input-multiple-output (MIMO) system with the aim of maintaining reasonable complexity. This goal is achieved by combining the two proposed algorithms, beam search and path-antenna pairing algorithms. The beam search algorithm identifies the radio paths of all UEs to the RIS by sweeping the beams of the RIS. Then, the path-antenna pairing algorithm allocates the strongest radio path between each UE and the RIS to one of the BAs by controlling an RIS beam to direct the signal from that path to the BA. Finally, we have built a real-time testbed to experiment with the proposed RIS-integrated BS-based uplink MIMO system. Numerical results, including experimental data, validate the effectiveness of the proposed RIS-integrated BS-based uplink MIMO system.

To enable high-tech lifestyles in the near future, trillions of connected low-power internet of things (IoT) devices should perpetually operate to meet the high-demand requirements of the users. Simultaneous wireless information and power transfer (SWIPT) is an indispensable technology for guaranteeing the endurable operation of massive IoT devices. Reconfigurable intelligent surface (RIS) is currently emerging as a cost-effective and energy-efficient solution for controlling wireless communication environments to enhance the quality of service. In this paper, we propose an efficient beam-sharing algorithm (BSA) designed for SWIPT systems that incorporate RIS to realize the coexistence of wireless power and information. The considered RIS-assisted SWIPT system consists of one RIS, one data transmitter (DTx), one power transmitter (PTx), one data user (DU), and one power user (PU). Since the required power for the power transfer is radically higher than that for the information transmission, the high power signal leaked from the PTx can cause fatal damage to data transmission and sensitive electronic components (e.g., LNA) integrated with DU. Hence, we primarily aim to maximize the desired power transfer from PTx to PU while minimizing the leakage power (i.e., interference) delivered to the DU. Additionally, the algorithm maximizes the quality of the information signal transmitted from DTx to DU. We then develop a simulator to verify the effectiveness of the proposed algorithm. We have investigated the performance of the proposed BSA algorithm with various quantization phase shifts (i.e., 1-bit, 2-bit, 3-bit, and continuous phase). A suppression ranging between 15 dB and 38 dB is witnessed in all simulation scenarios, while the DTx-DU power and PTx-PU power are simultaneously maximized in the simulated scenario. For further confirmation, we have built a real-life RIS-assisted SWIPT testbed and validated the proposed BSA algorithm. Experimental results indicate that the proposed BSA algorithm successfully delivers the maximum power/signal from PTx/DTx to PU/DU while limiting the interference signal sent by PTx to the DU to ensure robust and reliable data transmission.

Simultaneous wireless information and power transfer (SWIPT) is a key technology for enabling future high-tech lifestyles by guaranteeing the perpetual operation of trillions of low-power IoT devices. Currently, reconfigurable intelligent surface (RIS) is a promising technology for achieving cost- effective and energy-efficient wireless technologies. In this paper, we propose an efficient beam-sharing algorithm for RIS-aided SWIPT systems. The proposed algorithm maximizes the power transferred from the power transmitter (Ptx) to the power user (PU) while minimizing that to the data user (DU) but maximizing the signal from the data transmitter (Dtx) to DU. Simulation results demonstrate that the proposed beam-sharing algorithm effectively delivers power from Ptx to PU while limiting the power sent by Ptx to DU but maximizing the received signal from Dtx.

This article proposes a sparsity-aware channel estimation scheme for reconfigurable intelligent surface (RIS)-assisted wireless communications. We present an angular domain-channel sparsity model in a closed-form mathematical expression. A comprehensive formulation of the RIS channel estimation problem based on the sparsity analysis and RIS reflection model is also presented in this manuscript. This work aims to achieve a practical RIS beamforming algorithm without requiring excessive training overhead or any sensor deployment. We achieve the goal by proposing two sparsity-aware RIS channel estimation schemes based on the compressive sensing (CS) algorithms, such as the Dantzig selector (DS) and orthogonal matching pursuit (OMP). Differently from the existing works on the CS algorithms for RIS, we consider a fully passive RIS without any active sensor. We validate the theory and algorithm through both simulations and experiments. We have experimented orthogonal frequency-division multiplexing (OFDM) communications on our 5.8-GHz 1-bit RIS testbed with QPSK, 16QAM, 64QAM, and 256QAM modulation schemes. By experiments, it is shown that the proposed scheme is able to adaptively form a beam toward the receiver and improves the quality of the wireless communication to a notable level. Thanks to the properties of the proposed scheme, the wireless channel can be estimated without excessive training time and complexity.

Recently, reconfigurable intelligent surface (RIS) has drawn massive attention among researchers and entrepreneurs as a potential technology for next-generation wireless technologies. This paper proposes a beam splitting method to simultaneously deliver power and information to different users (i.e., power user/information user). We use orthogonal training patterns generated by the Hadamard matrix to estimate the end-to-end channel information of each user. Then, a pattern addition (PA) method is applied to split the beam for each user. We implement a real-life testbed of the RIS-aided simultaneous wireless information and power transfer (SWIPT) system to verify the proposed algorithm. By experiment, we show that the proposed method can effectively distribute power and information to the corresponding users.

Recently, reconfigurable intelligent surface (RIS) with passive beamforming capability is emerging as a potential technology for wireless power transfer (WPT) applications thanks to its cost-effective and energy-efficient features. This work studies multifocus techniques for RIS-aided WPT systems to simultaneously and adaptively charge multiple Internet of Things (IoT) devices in the Fresnel zone. In particular, we propose three multifocus methods, which are pattern addition (PA), random unit cell interleaving (RUI), and RIS tile division (RTD), for enabling multifocus RIS-aided WPT applications. We elaborate the algorithms for computing the RIS reflection phases for all methods. The proposed methods can balance the power levels of beams focused on multiple receivers by controlling weight factors. Furthermore, we have implemented a real-life RIS-aided WPT testbed to verify these proposed methods. The system consists of a phased antenna array transmitter, two receivers, and a 1-bit RIS with 512 unit cells. The WPT experiments have been performed in several test scenarios to show the effectiveness of the proposed techniques. The experiment results demonstrate that the proposed schemes effectively generate multiple focusing beams with adjustable power levels toward the desired receivers.

Reconfigurable intelligent surface (RIS) is a promising technology for radio-frequency wireless power transfer (WPT) as it is capable of beamforming and beam focusing without using active and power-hungry components. In this article, we propose a multitile RIS beam scanning (MTBS) algorithm for powering up Internet of Things (IoT) devices. Considering the hardware limitations of the IoT devices, the proposed algorithm requires only power information to enable the beam focusing capability of the RIS. Specifically, we first divide the RIS into smaller RIS tiles. Then, all RIS tiles and the phased array transmitter are iteratively scanned and optimized to maximize the receive power. We elaborately analyze the proposed algorithm and build a simulator to verify it. Furthermore, we have built a real-life testbed of RIS-aided WPT systems to validate the algorithm. The experimental results show that the proposed MTBS algorithm can properly control the transmission phase of the transmitter and the reflection phase of the RIS to focus the power at the receiver. Consequently, after executing the algorithm, about 20-dB improvement of the receive power is achieved compared to the case that all unit cells of the RIS are in OFF state. By experiments, we confirm that the RIS with the MTBS algorithm can greatly enhance the power transfer efficiency.

We propose a battery-less location tracking system that enables 3-D positioning of an Internet of Things (IoT) device powered by the radio frequency (RF) wireless power transfer (WPT). In the proposed system, a power beacon is equipped with a phased antenna array that has the dual purposes of high-efficiency WPT and phase-based accurate positioning. In order to enhance the efficiency of the RF WPT, we propose a beam focusing algorithm that dynamically controls the respective phases of antenna elements to place the focal point of the electro-magnetic (EM) wave onto the target IoT device. We also propose a phase-based positioning algorithm that requires only one multi-antenna anchor point for determining the distance as well as the direction from the anchor point. We analyze the Cramer-Rao lower bound (CRLB) of the phase-based positioning with a single multi-antenna anchor point, and show that the distance from the anchor point can be estimated as long as the IoT device lies within the radiative near-field region. We propose a joint location tracking and WPT algorithm that performs 3-D positioning and beam-focused WPT in a unified way. We have built a real-life testbed with a large-scale antenna array with 64 antenna elements for testing the proposed algorithm. The experimental results show the effectiveness of the proposed algorithm in a real environment.