Extremely large-scale reconfigurable intelligent surface (XL-RIS) can effectively overcome severe fading and provide higher communication performance. However, current research on XL-RIS overlooks the discrete phase-shift characteristics of RIS in practical systems, which will result in significant performance degradation. In this paper, we investigate near-field communication schemes assisted by XL-RIS with discrete phase shifts. Specifically, we propose a hierarchical beam training method to obtain the user channel state information (CSI), and develop the jointly optimized codebook construction (JOCC) method and separately optimized codebook construction (SOCC) method for base station (BS) precoding and XL-RIS phase shifts, respectively. With JOCC, the most superior beam training performance can be obtained. With SOCC, higher performance than the single-antenna BS codebook can be obtained at a similar complexity. Further, we propose a flexible multiuser interference management (IM) method that is simple to solve. The IM method uses adaptive gain matrix approximation to take into account user fairness and can be solved in closed-form iterations. In addition, we extend the proposed method to a hybrid precoding design. Simulation results demonstrate that the proposed multi-resolution codebook construction method can obtain more accurate beam patterns and user CSI, and the proposed IM method obtains superior performance over the benchmark methods.

Stacked intelligent metasurfaces (SIM) provide a cost-effective and scalable solution for large-scale antenna communications. However, efficient channel state information acquisition and phase shift optimization remain critical challenges. In this paper, we develop a unified framework of low-complexity algorithms for SIM-assisted communication systems to address these issues. Specifically, we propose a generalized two-step codebook construction (TSCC) method that lever-ages two-dimensional angular-domain decoupling to transform planar array beamformer design into two independent one-dimensional linear array beamformer design problems, efficiently solved via the Gerchberg–Saxton algorithm and our proposed majorization–minimization-based proximal-distance (PDMM) algorithm. We further develop a two-stage coded-sliding beam training (TSCSBT) method for low-overhead and high-accuracy beam training, where error-correcting codes are embedded in the first-stage training to enhance robustness against noise, and sliding sampling is subsequently performed around the matched angular samples to improve angular resolution. The proposed framework is further extended to multi-path user channels. Finally, a variable decoupling-based block successive upper bound minimization (VD-BSUM) algorithm is proposed to directly solve the QoS-constrained sum-rate maximization problem through closed-form iterative updates with substantially reduced computational complexity. Simulation results demonstrate the effectiveness of the proposed methods in achieving precise beam pattern realization, improved beam training accuracy and angular resolution, and enhanced sum-rate performance.

Active reconfigurable intelligent surface (RIS) is a new RIS architecture that can reflect and amplify communication signals. It can provide enhanced performance gain compared to the conventional passive RIS systems that can only reflect the signals. On the other hand, the design problem of active RIS-aided systems is more challenging than the passive RIS-aided systems and its efficient algorithms are less studied. In this paper, we consider the sum rate maximization problem in the multiuser massive multiple-input single-output (MISO) downlink with the aid of a large-scale active RIS. Existing approaches for handling this problem usually resort to general optimization solvers and can be computationally prohibitive. We propose an efficient block successive upper bound minimization (BSUM) method, of which each step has a (semi) closed-form update. Thus, the proposed algorithm has an attractive low per-iteration complexity. By simulation, our proposed algorithm consumes much less computation than the existing approaches. In particular, when the MIMO and/or RIS sizes are large, our proposed algorithm can be orders-of-magnitude faster than existing approaches.

The combination of reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) is a promising technique to enhance spectral efficiency and energy efficiency. However, the imperfect channel state information (CSI) of the wireless channel and hardware impairments (HWI) of the radio frequency chain will cause significant performance loss on RIS-aided NOMA communication. In this paper, we focus on the effect of the imperfect CSI and generalized HWI on RIS-aided NOMA communication and propose an efficient robust precoding and phase shift design scheme to enhance the energy efficiency of systems. Specifically, we minimize the transmit power with quality of service constraints of users, where the imperfect CSI and generalized HWI are modeled as Gaussian error models, and the successful successive interference cancellation condition is characterized by the variance criterion. The minimization problem is greatly challenging due to the non-closed form outage constraints and non-explicit phase shift design. To solve it, we develop an efficient probabilistic technique to reformulate the outage constraints and restrict an explicit objective function to obtain a more efficient phase shift design. Numerical results demonstrate that our scheme has superior convergence performance, energy efficiency, and feasibility rate compared to existing schemes.

Reconfigurable intelligent surfaces (RIS) can dynamically reconstruct wireless environments to enhance spectral efficiency. However, most existing studies have ignored the impact of the phase error and imperfect amplitude gain of the RIS. In this paper, we investigate the practical RIS-aided multiuser communication systems by maximizing the sum of users’ average achievable rate, filling the current research gap. Specifically, a novel RIS phase shift design approach, namely amplitude feedback (AF), is proposed by utilizing the coupling relationship between the amplitude and phase to derive the optimal phase shift under the worst phase error. The feasibility of AF is demonstrated by proving the measurability of amplitude response through the electromagnetic theory. We propose a channel estimation design with low pilot overhead and provide an effective closed-form achievable rate to approximate the average achievable rate. Moreover, an efficient optimization algorithm is proposed to achieve the optimal closed-form precoding at the base station and the optimal trade-off design between the amplitude and phase of RIS, and the algorithm is extended to active RIS systems. Numerical results demonstrate that our proposed AF method and optimization algorithm can efficiently improve the performance in terms of achievable sum rate compared to existing methods.

Integrating reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) provides a promising solution to support large-scale secure communications. However, reducing the impact of transceiver hardware impairments (HWI) on the performance of RIS-aided NOMA secure networks remains a challenge. In this paper, we propose a robust transmission scheme for RIS-aided NOMA secure networks with transceiver HWI under two proposed eavesdropping scenarios and two artificial noise methods. A closed-form expression for the distortion noise power caused by transceiver HWI in NOMA networks is derived to quantify transceiver HWI. The sum secrecy rate of NOMA users with imperfect successive interference cancellation (SIC) is maximized under distortion noise for more robust security. Further, to tackle the resulting non-convex problem, we decompose it into two sub-problems. Both of them are converted into convex problems using the multi-dimensional quadratic transform (MDQT) method, semi-definite relaxation (SDR) technique, and the successive convex approximation (SCA) algorithm, and then employing the alternate optimization (AO) algorithm solve them. Numerical results demonstrate that the proposed scheme has superior security performance over orthogonal multiple access (OMA) networks, time division multiple access (TDMA) networks, and traditional NOMA networks, achieving more robust performance than the conventional scheme that ignores HWI and imperfect SIC.