Antenna Coding Optimization Based on Pixel Antennas for MIMO Wireless Power Transfer with DC Combining

This paper investigates antenna coding based on pixel antennas as a new degree of freedom for enhancing multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems. Antenna coding is closely related to the Fluid Antenna System (FAS) concept and further generalizes the radiation pattern reconfigurability. We first introduce a beamspace channel model to demonstrate reconfigurable radiation patterns enabled by antenna coders. By jointly optimizing the antenna coding and transmit beamforming with perfect channel state information (CSI), we exploit gains from antenna coding, transmit beamforming, and rectenna nonlinearity to maximize the output DC power. We adopt an alternating optimization approach with the quasi-Newton method and Successive Exhaustive Boolean Optimization (SEBO) method with warm-start to handle the transmit beamforming design and antenna coding design respectively. Finally, simulation results show that the proposed MIMO WPT system with pixel antennas achieves up to 15 dB gain in average output DC power compared with a conventional system with fixed antenna configuration, highlighting the potential of pixel antennas for boosting the WPT efficiency.

Cooperative Rotatable IRSs for Wireless Communications: Joint Beamforming and Orientation Optimization

Rotatable intelligent reflecting surfaces (IRSs) introduce a new degree of freedom (DoF) for shaping wireless propagation by adaptively adjusting the orientation of IRSs. This paper considers an angle-dependent reflection model in a wireless communication system aided by two rotatable IRSs. Specifically, we study the joint design of the base station transmit beamforming, as well as the cooperative passive beamforming and orientation of the two IRSs, to maximize the received signal-to-noise ratio (SNR). Under the light-of-sight (LoS) channels, we first develop a particle swarm optimization (PSO) based method to determine the IRS rotation and derive an optimal rotation in a closed-form expression for a two-dimensional IRS deployment. Then, we extend the design to the general Rician fading channels by proposing an efficient alternating optimization and PSO (AO-PSO) algorithm. Numerical results validate the substantial gains achieved by the IRS rotation over fixed-IRS schemes and also demonstrate the superior performance of the double rotatable IRSs over a single rotatable IRS given a sufficient total number of IRS elements.

Antenna Coding Design for Multi-User Transmissions Using Pixel Antennas

This work investigates exploiting the potential of pixel antennas, which are a reconfigurable antenna technology that can flexibly adjust the antenna characteristics through antenna coding, in multi-user transmissions. To that end, we propose a multi-user multi-input single-output (MISO) pixel antenna system, which deploys the pixel antenna at users, and develop the system model including pixel antenna with antenna coding and multi-user beamspace channels. Aiming at maximizing the sum rate performance, we first propose an algorithm to alternatively design the precoding at the transmitter and the antenna coding at users, which explores the performance boundary for the proposed multi-user MISO pixel antenna system. To reduce the computational complexity, we propose a codebook-based antenna coding design algorithm, where the antenna coder is online optimized from an offline codebook. To further enhance the computation efficiency, we propose a hierarchical codebook-based antenna coding design that uses a multi-layer hierarchical search to achieve a better performance-complexity trade-off. Simulation results show that, adopting the proposed algorithms, the multi-user MISO pixel antenna system can always outperform conventional multi-user MISO systems with fixed antennas. More importantly, results validate that the proposed (hierarchical) codebook-based algorithms can significantly reduce the computational complexity while maintaining a satisfactory sum rate performance.

Rotatable IRS Aided Wireless Communication

Rotatable intelligent reflecting surface (IRS) introduces a new spatial degree of freedom (DoF) by dynamically adjusting orientations without the need of changing its elements' positions in real time. To unleash the full potential of rotatable IRSs for wireless communications, this paper investigates the joint optimization of IRS rotation angles to maximize the minimum expected signal-to-noise ratio (SNR) over all locations within a given target area. We first propose an angle-dependent channel model that accurately characterizes the reception and reflection of each IRS element. Different from the conventional cosine-law assumption, the proposed model captures the practical electromagnetic characteristics of the IRS, including the effective reception area and reflection efficiency. For the single target location case, a particle swarm optimization (PSO)-based algorithm is developed to solve the SNR maximization problem, and a closed-form expression for a near-optimal solution is derived to provide useful insights. For the general area coverage enhancement case, the optimal rotation is obtained through a two-loop PSO-based iterative algorithm with null-point detection. In this algorithm, the outer loop updates the global rotation angles to maximize the minimum SNR over the target area, whereas the inner loop evaluates the SNR distribution within the area to identify the location corresponding to the minimum SNR through null-point detection. Numerical results demonstrate significant SNR improvement achieved by the proposed rotatable IRS design over various benchmark schemes under different system setups.

RIS-Assisted NOMA with Partial CSI and Mutual Coupling: A Machine Learning Approach

Non-orthogonal multiple access (NOMA) is a promising multiple access technique. Its performance depends strongly on the wireless channel property, which can be enhanced by reconfigurable intelligent surfaces (RISs). In this paper, we jointly optimize base station (BS) precoding and RIS configuration with unsupervised machine learning (ML), which looks for the optimal solution autonomously. In particular, we propose a dedicated neural network (NN) architecture RISnet inspired by domain knowledge in communication. Compared to state-of-the-art, the proposed approach combines analytical optimal BS precoding and ML-enabled RIS, has a high scalability to control more than 1000 RIS elements, has a low requirement for channel state information (CSI) in input, and addresses the mutual coupling between RIS elements. Beyond the considered problem, this work is an early contribution to domain knowledge enabled ML, which exploit the domain expertise of communication systems to design better approaches than general ML methods.

A Tutorial on Beyond-Diagonal Reconfigurable Intelligent Surfaces: Modeling, Architectures, System Design and Optimization, and Applications

Written by its inventors, this first tutorial on Beyond-Diagonal Reconfigurable Intelligent Surfaces (BD-RISs) provides the readers with the basics and fundamental tools necessary to appreciate, understand, and contribute to this emerging and disruptive technology. Conventional (Diagonal) RISs (D-RISs) are characterized by a diagonal scattering matrix $\mathbf{\Theta}$ such that the wave manipulation flexibility of D-RIS is extremely limited. In contrast, BD-RIS refers to a novel and general framework for RIS where its scattering matrix is not limited to be diagonal (hence, the ``beyond-diagonal'' terminology) and consequently, all entries of $\mathbf{\Theta}$ can potentially help shaping waves for much higher manipulation flexibility. This physically means that BD-RIS can artificially engineer and reconfigure coupling across elements of the surface thanks to inter-element reconfigurable components which allow waves absorbed by one element to flow through other elements. Consequently, BD-RIS opens the door to more general and versatile intelligent surfaces that subsumes existing RIS architectures as special cases. In this tutorial, we share all the secret sauce to model, design, and optimize BD-RIS and make BD-RIS transformative in many different applications. Topics discussed include physics-consistent and multi-port network-aided modeling; transmitting, reflecting, hybrid, and multi-sector mode analysis; reciprocal and non-reciprocal architecture designs and optimal performance-complexity Pareto frontier of BD-RIS; signal processing, optimization, and channel estimation for BD-RIS; hardware impairments (discrete-value impedance and admittance, lossy interconnections and components, wideband effects, mutual coupling) of BD-RIS; benefits and applications of BD-RIS in communications, sensing, power transfer.

A Hybrid Transmitting and Reflecting Beyond Diagonal Reconfigurable Intelligent Surface with Independent Beam Control and Power Splitting

A hybrid transmitting and reflecting beyond diagonal reconfigurable intelligent surface (BD-RIS) design is proposed. Operating in the same aperture, frequency band and polarization, the proposed BD-RIS features independent beam steering control of its reflected and transmitted waves. In addition it provides a hybrid mode with both reflected and transmitted waves using tunable power splitting between beams. The BD-RIS comprises two phase reconfigurable antenna arrays interconnected by an array of tunable two-port power splitters. The two-port power splitter in each BD-RIS cell is built upon a varactor in parallel with a bias inductor to exert tunable impedance variations on transmission lines. Provided with variable reverse DC voltages, the two-port power splitter can control the power ratio of S11 over S21 from -20 dB to 20 dB, thus allowing tunable power splitting. Each antenna is 2-bit phase reconfigurable with 200 MHz bandwidth at 2.4 GHz so that each cell of BD-RIS can also achieve independent reflection and transmission phase control. To characterize and optimize the electromagnetic response of the proposed BD-RIS design, a Th\'evenin equivalent model and corresponding analytical method is provided. A BD-RIS with 4 by 4 cells was also prototyped and tested. Experiments show that in reflection and transmission mode, the fabricated BD-RIS can realize beam steering in reflection and transmission space, respectively. It is also verified that when operating in hybrid mode, the BD-RIS enables independent beam steering of the reflected and transmitted waves. This work helps fill the gap between realizing practical hardware design and establishing an accurate physical model for the hybrid transmitting and reflecting BD-RIS, enabling hybrid transmitting and reflecting BD-RIS assisted wireless communications.

Antenna Coding Empowered by Pixel Antennas

Pixel antennas, based on discretizing a continuous radiation surface into small elements called pixels, are a flexible reconfigurable antenna technology. By controlling the connections between pixels via switches, the characteristics of pixel antennas can be adjusted to enhance the wireless channel. Inspired by this, we propose a novel technique denoted antenna coding empowered by pixel antennas. We first derive a physical and electromagnetic based communication model for pixel antennas using microwave multiport network theory and beamspace channel representation. With the model, we optimize the antenna coding to maximize the channel gain in a single-input single-output (SISO) pixel antenna system and develop a codebook design for antenna coding to reduce the computational complexity. We analyze the average channel gain of SISO pixel antenna system and derive the corresponding upper bound. In addition, we jointly optimize the antenna coding and transmit signal covariance matrix to maximize the channel capacity in a multiple-input multiple-output (MIMO) pixel antenna system. Simulation results show that using pixel antennas can enhance the average channel gain by up to 5.4 times and channel capacity by up to 3.1 times, demonstrating the significant potential of pixel antennas as a new dimension to design and optimize wireless communication systems.

Cooperative Integrated Sensing and Communication Networks: Analysis and Distributed Design

This paper proposes a cooperative integrated sensing and communication network (Co-ISACNet) adopting hybrid beamforming (HBF) architecture, which improves both radar sensing and communication performance. The main contributions of this work are four-fold. First, we introduce a novel cooperative sensing method for the considered Co-ISACNet, followed by a comprehensive analysis of this method. This analysis mathematically verifies the benefits of Co-ISACNet and provides insightful design guidelines. Second, to show the benefits of Co-ISACNet, we propose to jointly design the HBF to maximize the network communication capacity while satisfying the constraint of beampattern similarity for radar sensing, which results in a highly dimensional and non-convex problem. Third, to facilitate the joint design, we propose a novel distributed optimization framework based on proximal gradient and alternating direction method of multipliers, namely PANDA. Fourth, we further adopt the proposed PANDA framework to solve the joint HBF design problem for the Co-ISACNet. By using the proposed PANDA framework, all access points (APs) optimize the HBF in parallel, where each AP only requires local channel state information and limited message exchange among the APs. Such framework reduces significantly the computational complexity and thus has pronounced benefits in practical scenarios. Simulation results verify the effectiveness of the proposed algorithm compared with the conventional centralized algorithm and show the remarkable performance improvement of radar sensing and communication by deploying Co-ISACNet.

Channel Estimation and Beamforming for Beyond Diagonal Reconfigurable Intelligent Surfaces

Beyond diagonal reconfigurable intelligent surface (BD-RIS) is a new advance and generalization of the RIS technique. BD-RIS breaks through the isolation between RIS elements by creatively introducing inter-element connections, thereby enabling smarter wave manipulation and enlarging coverage. However, exploring proper channel estimation schemes suitable for BD-RIS aided communication systems still remains an open problem. In this paper, we study channel estimation and beamforming design for BD-RIS aided multi-antenna systems. We first describe the channel estimation strategy based on the least square (LS) method, derive the mean square error (MSE) of the LS estimation, and formulate the joint pilot sequence and BD-RIS design problem with unique constraints induced by BD-RIS architectures. Specifically, we propose an efficient pilot sequence and BD-RIS design which theoretically guarantees to achieve the minimum MSE. With the estimated channel, we then consider two BD-RIS scenarios and propose beamforming design algorithms. Finally, we provide simulation results to verify the effectiveness of the proposed channel estimation scheme and beamforming design algorithms. We also show that more interelement connections in BD-RIS improves the performance while increasing the training overhead for channel estimation.