Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology for wireless communications, which intelligently controls the phase shift of each unit cell to form desired ...beams. Most prior works on RIS consider time-division duplexing (TDD) systems, in which the same phase shifts can be applied to both uplink and downlink due to the channel reciprocity. However, for frequency-division duplexing (FDD) systems, using the same phase shifts will result in beam misalignment, thereby leading to performance degradation. To address this issue, in this paper, we study the practical RIS design and beamforming optimization for FDD systems. By representing the phase shifts of RIS with the equivalent circuit model which includes the resistance, inductances, and tunable capacitance, we propose a methodology to design the circuit parameters (i.e., inductances and capacitance) to meet the desired reflection requirements (i.e., phase tuning range, reflectivity, and zero phase slope) of both the uplink and downlink transmissions in FDD systems. Given the designed inductances, a practical binary RIS reflection model corresponding to two reflection states is then proposed. Furthermore, based on the proposed reflection model, a problem is formulated to jointly optimize the active and passive beamforming such that the minimum array response gain of the uplink and the downlink is maximized. An efficient iterative algorithm is proposed to obtain a suboptimal solution. Simulation results show that our proposed RIS design outperforms those benchmarks which design the circuits by only optimizing either uplink or downlink.
This paper provides a theoretical framework for understanding the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) with zero-forcing (ZF) ...detectors under imperfect channel state information (CSI). We first introduce a low-overhead minimum mean square error (MMSE) channel estimator, and then derive and analyze closed-form expressions for the uplink achievable rate. Our analytical results demonstrate that: 1) regardless of the RIS phase shift design, the rate of all users scales at least on the order of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}\left ({\log _{2}\left ({MN}\right)}\right) </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">N </tex-math></inline-formula> are the numbers of antennas and reflecting elements, respectively; 2) by aligning the RIS phase shifts to one user, the rate of this user can at most scale on the order of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}\left ({\log _{2}\left ({MN^{2}}\right)}\right) </tex-math></inline-formula>; 3) either <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula> or the transmit power can be reduced inversely proportional to <inline-formula> <tex-math notation="LaTeX">N </tex-math></inline-formula>, while maintaining a given rate. Furthermore, we propose two low-complexity majorization-minimization (MM)-based algorithms to optimize the sum user rate and the minimum user rate, respectively, where closed-form solutions are obtained in each iteration. Finally, simulation results validate the accuracy of all derived analytical results. Our simulation results also show that the maximum sum rate can be closely approached by simply aligning the RIS phase shifts to an arbitrary user.
Reconfigurable intelligent surfaces (RISs) have drawn considerable attention due to their ability to direct electromagnetic waves into desirable directions. Although RISs share some similarities with ...relays, the two have fundamental differences impacting their performance. To harness the benefits of both, we propose a downlink system wherein a relay and an RIS improve performance in terms of energy-efficiency. Using singular value decomposition (SVD), semidefinite programming (SDP), and function approximations, we propose different solutions for optimizing the beamforming matrices at the base-station (BS), the relay, and the phase shifts at the RIS to minimize the total power under quality-of-service (QoS) constraints. The problem is solved when the relay operates in half-duplex and full-duplex modes and when the reflecting elements have continuous and discrete phase shifts. Simulation results compare the performance of the system with and without the RIS or the relay, under different optimization solutions. The results show that the system with full-duplex relay and RIS outperforms the other scenarios, and the contribution of full-duplex relay is higher than that of the RIS. However, an RIS outperforms a half-duplex relay when the required QoS is high. The results also show that increasing the number of reflecting elements improves the performance better in the presence of a relay than in its absence.
Recently, atomic norm minimization (ANM) has been applied in the reconfigurable intelligent surface (RIS) aided direction of arrival (DOA) estimation problem in the non-line-of-sight (NLOS) ...propagation. However, most existing RIS-aided ANM (RIS-ANM) methods assume a uniform linear array (ULA) RIS which can only handle the one-dimensional (1D) DOA estimation. To this end, a novel RIS-aided gridless two-dimensional (2D) DOA estimation method is developed for a uniform planar array (UPA) RIS passive sensing system, where a general single-input multi-output (SIMO) transmission model is adopted. Specifically, a RIS-aided decoupled ANM (RIS-D-ANM) is proposed for gridless 2D-DOA retrieval. We show that the proposed RIS-D-ANM provides a decoupled formulation of the atomic norm instead of reshaping the 2D information via vectorization in the classic RIS-ANM method. Thus, the computational complexity of the original high-dimensional SDP problem is remarkably reduced without performance degradation. Furthermore, the computational cost is further reduced by integrating the alternating direction method of multiplier (ADMM), resulting in the RIS-aided decoupled ADMM (RIS-D-ADMM) method. Simulation results demonstrate the effectiveness of the proposed method.
This paper investigates a multiuser reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) system, in which a RIS assists in establishing ...favorable wireless communication environment. Particularly, we study the max-min signal-to-interference-plus-noise ratio (SINR) problem of the system by joint optimizing the base station (BS) active beamforming vectors, the RIS passive beamforming vector, and the power splitting (PS) ratios while guaranteeing the BS maximum transmit power budget and the minimum harvested energy threshold. The considered max-min SINR problem is highly non-convex, which is arduous to directly solve. Hence, we present an efficient alternating optimization (AO) algorithm to decompose the max-min SINR problem into three tractable subproblems, which are solved in an alternating manner. Particularly, we apply semi-definite relaxation (SDR) technique and the bisection method to tackle the beamforming optimization subproblems, and then derive a closed-form solution to solve the PS ratios optimization subproblem. Numerical simulations verify the superiority of our proposed AO algorithm and demonstrate that deploying RIS can achieve significantly increased min-SINR value.
Reconfigurable intelligent surface (RIS) has emerged as a promising technology for enhancing the performance of wireless communication systems. However, the extent of this enhancement has yet to be ...defined in a simple and insightful manner, especially when RIS amplitude and phase responses are coupled. In this paper, we characterize the fundamental ergodic capacity limits of RIS-aided multiple-input multiple-output (MIMO), a.k.a. MIMO-RIS, when considering a practical amplitude response for the RIS, which is coupled to its phase shift response. By studying these fundamental limits, we provide insights into the performance of MIMO-RIS systems and inform the design and optimization of future wireless communications. Accordingly, we first derive a novel expression of MIMO-RIS ergodic capacity from a closed-form expression of the probability density function (pdf) of the cascaded channel eigenvalues. We then provide upper and lower bounds, alongside low SNR, high SNR, and large number of RIS element approximations to illustrate the dependence of the MIMO-RIS ergodic capacity on the amplitude and phase of RIS elements. These expressions helped us to define the maximum SNR gain of MIMO-RIS over MIMO systems. Next, simulations are used to validate the accuracy and correctness of our various capacity expressions. Furthermore, we investigate the impact of environmental factors, such as near-field or far-field path loss, on the MIMO-RIS ergodic capacity. Numerical results confirm the accuracy of our MIMO-RIS SNR gain expression and provide valuable insights into the performance of RIS-based systems in realistic scenarios. Consequently, this can contribute to the design of future wireless communications based on MIMO-RIS.
Passive tags in bistatic backscatter networks have a myriad of industry applications. However, due to insufficient energy harvesting (EH), tags have poor communication ranges, activation distances, ...and data rates. To overcome these challenges, we employ a reconfigurable intelligent surface (RIS) to enhance the incident radio frequency power at the tag. We consider linear and non-linear EH models and analyze single-tag and multi-tag scenarios. For single-tag networks, we optimize the RIS phase shifts to maximize the incident power at the tag and the signal-to-noise ratio of the reader. Key metrics, such as received power, harvested power, achievable rate, outage probability, bit error rate, and diversity order, are also derived. The impact of RIS phase shift quantization errors is also studied. For the multi-tag case, an algorithm to compute the optimal RIS phase shifts is developed. Numerical results and simulations demonstrate significant improvements compared to the benchmarks of no-RIS case and random RIS-phase design. For instance, our optimal design with a 200-element RIS increases the activation distance of tags by 270% and 55% compared to those benchmarks. In summary, the proposed RIS solution improves the energy autonomy of tags while keeping the basic tag design intact.
Reconfigurable Intelligent Surface (RIS)-assisted communication systems can employ phase shifters to focus radiation energy at the receiver, thereby enhancing link quality and extending coverage. ...However, designing phase shifters requires cascaded channel state information (CSI), which poses a challenge due to the absence of A/D and D/A converters at RIS nodes. In RIS-assisted orthogonal frequency division multiplexing (OFDM) systems, the design becomes particularly intricate since all subcarriers of an RIS element can only share the same phase shifter. Consequently, the estimation process relies on numerous pilots to provide sufficient degrees of freedom for CSI estimation, significantly increasing the pilot overhead. In this paper, we investigate several low-complexity and low pilot-overhead channel estimation methods for RIS-assisted single-input multiple-output (SIMO) OFDM systems based on compressive sensing techniques. Our study commences by developing a low-complexity orthogonal matching pursuit (OMP) estimator, which jointly estimates sparse time-domain channel impulse responses (CIRs) and their associated sparse angular domains. The OMP-based estimator exhibits very low complexity but is sensitive to the structure of the sensing matrix. Therefore, we introduce two low-complexity sparse Bayesian learning (SBL) channel estimators to enhance robustness to the sensing matrix structure. The first estimator employs approximate message passing (AMP) with unitary transformation (SBL-UTAMP), while the second estimator uses orthogonal AMP (SBL-OAMP). Simulation results indicate that our proposed methods achieve a promising balance between CSI estimation performance and complexity in RIS-assisted SIMO-OFDM systems.
Reconfigurable intelligent surface (RIS) is an excellent use case for line-of-sight (LOS) based technologies such as free-space optical (FSO) communications. In this paper, we analyze the performance ...of RIS-empowered FSO (RISE-FSO) systems by unifying Fisher-Snedecor (<inline-formula> <tex-math notation="LaTeX">{\mathcal{F}} </tex-math></inline-formula>), Gamma-Gamma (<inline-formula> <tex-math notation="LaTeX">\cal {GG} </tex-math></inline-formula>), and Malága (<inline-formula> <tex-math notation="LaTeX">\cal {M} </tex-math></inline-formula>) distributions for atmospheric turbulence with zero-boresight pointing errors over deterministic as well as random path-loss in foggy conditions with heterodyne detection (HD) and intensity modulation/direct detection (IM/DD) methods. By deriving the probability density function (PDF) and cumulative distribution function (CDF) of the direct-link (DL) with the statistical effect of atmospheric turbulence, pointing errors and random fog, we develop exact expressions of PDF and CDF of the resultant channel for the RISE-FSO system. Using the derived statistical results, we present exact expressions of outage probability, average bit-error-rate (BER), ergodic capacity, and moments of signal-to-noise ratio (SNR) for both DL-FSO and RISE-FSO systems. We also develop an asymptotic analysis of the outage probability and average BER and derive the diversity order of the considered systems. We validate the analytical expressions using Monte-Carlo simulations and demonstrate the performance scaling of the FSO system with the number of RIS elements for various turbulence channels, detection techniques, and weather conditions.
This article proposes a distributed intelligent Coordinated Multi-Point Non-Orthogonal Multiple-Access (CoMP-NOMA) collaborative transmission model with the assistance of reconfigurable intelligent ...surfaces (RISs) to address the issues of poor communication quality, low fairness, and high system power consumption for edge users in multi-cellular networks. By analyzing the interaction mechanisms and influencing factors among RIS signal enhancement, NOMA user scheduling, and multi-point collaborative transmission, the model establishes RIS-enhanced edge user grouping and coordinates NOMA user clusters based on this. In the multi-cell RIS-assisted JT-CoMP NOMA downlink transmission, joint optimization of the power allocation (PA), user clustering (UC), and RIS phase-shift matrix design (PS) poses a challenging Mixed-Integer Non-Linear Programming (MINLP) problem. The original problem is decomposed by optimizing the formulas into joint sub-problems of PA, UC, and PA and PS, and solved using an alternating optimization approach. Simulation results demonstrate that the proposed scheme effectively reduces the system’s power consumption while significantly improving the system’s throughput and rates.
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