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Reconfigurable intelligent surfaces (RISs) are a new and emerging technology that has the potential to revolutionize the way that wireless communication systems are designed and implemented. These surfaces are made up of a large number of small, individually controllable elements, each of which can be used to manipulate the phase and amplitude of the electromagnetic waves that pass through it. This allows them to perform a wide range of functions, including wireless power transfer, beamforming, and cloaking. In this work, we provide an overview of the principles and applications of reconfigurable intelligent surfaces, and we discuss the advantages and challenges of these surfaces in wireless communications. We also provide an overview of the current state of research in this area. Moreover, we outline the future directions for the development of these surfaces. [ABSTRACT FROM AUTHOR]

Recently, reconfigurable intelligent surfaces have an increasing role to enhance the coverage and quality of mobile networks especially when the received signal level is very weak because of obstacles and random fluctuation. This motivates the researchers to add more contributions to the fields of reconfigurable intelligent surfaces (RIS) in wireless communications. A substantial issue in reconfigurable intelligent surfaces is the huge overhead for channel state information estimation which limits the system's performance, oppressively. In this work, a newly proposed method is to estimate the angle of arrival and path loss at the RIS side and then send short information to the base station rather than huge overhead as in previous research. The estimated channel state information is used to beamform the downlink waveform toward users accurately. The simulation results indicate that the proposed algorithm calculated the angle of arrival of users, admirably especially at a high signal-to-noise ratio. Moreover, a considerable spectral efficiency enhancement is obtained as compared to the traditional methods. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RIS) are considered of paramount importance to improve air–ground and THz communications performance for 6G systems. Recently, RISs were proposed in Physical Layer Security (PLS), as they can (i) improve the secrecy capacity due to the controlled directional reflections' capability of RIS elements and (ii) avoid potential eavesdroppers, redirecting data streams towards the intended users. This paper proposes the integration of a multi-RISs system within a Software Defined Networking (SDN) architecture to provide a specific control layer for secure data flows forwarding. The optimisation problem is properly characterised in terms of an objective function and an equivalent graph theory model is considered to address the optimal solution. Moreover, different heuristics are proposed, trading off complexity and PLS performance, to evaluate the more suitable multi-beam routing strategy. Numerical results are also provided, focusing on a worst case scenario which points out the improvement of the secrecy rate from the increase in the number of eavesdroppers. Furthermore, the security performance is investigated for a specific user mobility pattern in a pedestrian scenario. [ABSTRACT FROM AUTHOR]

The goal of 6G is to make far-reaching changes in communication systems with stricter demands, such as high throughput, extremely low latency, stronger security, and ubiquitous connectivity. Several promising techniques, such as reconfigurable intelligent surfaces (RISs), have been introduced to achieve these goals. An RIS is a 2D low-cost array of reflecting elements that can adjust the electromagnetic properties of an incident signal. In this paper, we guarantee secrecy by using an irregular RIS (IRIS). The main idea of an IRIS is to irregularly activate reflecting elements for a given number of RIS elements. In this work, we consider a communication scenario in which, with the aid of an IRIS, a multi-antenna base station establishes a secure link with a legitimate single-antenna user in the presence of a single-antenna eavesdropper. To this end, we formulate a topology-and-precoding optimization problem to maximize the secrecy rate. We then propose a Tabu search-based algorithm to jointly optimize the RIS topology and the precoding design. Finally, we present simulation results to validate the proposed algorithm, which highlights the performance gain of the IRIS in improving secure transmissions compared to an RIS. Our results show that exploiting an IRIS can allow additional spatial diversity to be achieved, resulting in secrecy performance improvement and overcoming the limitations of conventional RIS-assisted systems (e.g., a large number of active elements). [ABSTRACT FROM AUTHOR]

In this paper, an unmanned aerial vehicle (UAV) nonorthogonal multiple access (NOMA) system operating in millimeter-wave (mmWave) communications under the aid of multiple reconfigurable intelligent surfaces (RISs) is determined. Specifically, two NOMA users receive messages from UAV via both UAV-RISs-user and UAV-user links using mmWave communications. The closed-form expressions of outage probabilities (OPs) and achievable data rates (ADRs) are successfully derived over Nakagami-m fading channels to investigate the performance of the RISs aided UAV-NOMA-mmWave system. Computer simulations are provided to validate the derived expressions. Numerical results observe that by utilizing RISs, the OPs and ADRs performance of UAV-NOMA-mmWave system is significantly improved in comparison with the case without RISs. More specifically, even with high altitude of UAV (300 m) and high carrier frequency (50 GHz), the OPs of UAV-NOMA-mmWave system with RISs are remarkably lower than those without RISs. Meanwhile, the ADRs with RISs are only higher than those without RISs in low transmit power of UAV. In high transmit power of UAV, ADRs with and without RISs are similar due to the NOMA characteristics. Besides the distances and carrier frequency, the effects of other parameters such as the position of RISs, the number of reflecting elements (REs), and the altitude of UAVs are clarified to obtain the system behaviors. [ABSTRACT FROM AUTHOR]

Wireless networks in agricultural environments are unique in many ways. Recent measurements reveal that the dynamics of crop growth impact wireless propagation channels with a long-term seasonal pattern. Additionally, short-term environmental factors, such as strong wind, result in variations in channel statistics. Next-generation agricultural fields, populated by autonomous tractors, drones, and high-throughput sensing systems, require high-throughput connectivity infrastructure, resulting in the future deployment of high-frequency networks, where they have not been deployed before. More specifically, when millimeter-wave (mmWave) communication systems, a viable candidate for 5G and 6G high-throughput solutions, are deployed for higher throughput, these issues become more prominent due to the relatively small wavelength at this frequency band. To improve coverage in the mmWave spectrum in agricultural settings, reconfigurable intelligent surfaces (RISs) are a promising solution with low energy consumption and high cost efficiency when compared to half-duplex active relays with multiple antennas. To ensure link resiliency under dynamic channel behavior, an adaptive RIS for broadband wireless agricultural networks (AgRIS) at mmWave band is designed in this work. AgRIS relies on output from a time-series model that forecasts the short-term wind speed based on measured wind data, which is readily available in most farms. The temporal correlation between link reliability and wind speed is demonstrated through extensive field experiments. Our simulation results demonstrate that AgRIS with a small footprint of 11 × 11 elements can help mitigate the adversarial effects of wind-induced signal level drop by up to 8 dB and provides high energy efficiency of 1 Gbits/joule.

Reconfigurable intelligent surfaces (RIS) offer the potential to customize the radio propagation environment for wireless networks, and will be a key element for 6G communications. However, due to the unique constraints in these systems, the optimization problems associated to RIS configuration are challenging to solve. This paper illustrates a new approach to the RIS configuration problem, based on the use of artificial intelligence (AI) and deep learning (DL) algorithms. Concretely, a custom convolutional neural network (CNN) intended for edge computing is presented, and implementations on different representative edge devices are compared, including the use of commercial AI-oriented devices and a field-programmable gate array (FPGA) platform. This FPGA option provides the best performance, with ×20 performance increase over the closest FP32, GPU-accelerated option, and almost ×3 performance advantage when compared with the INT8-quantized, TPU-accelerated implementation. More noticeably, this is achieved even when high-level synthesis (HLS) tools are used and no custom accelerators are developed. At the same time, the inherent reconfigurability of FPGAs opens a new field for their use as enabler hardware in RIS applications.

This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present context of cellular networks, device-to-device (D2D) communication stands out as a promising technique to enhance the spectrum efficiency. Simultaneously, RIS have gained considerable attention due to their ability to enhance the quality of dynamic wireless networks by maximizing the spectrum efficiency without increasing the power consumption. However, prevalent centralized D2D transmission schemes require global information, leading to a significant signaling overhead. Conversely, existing distributed schemes, while avoiding the need for global information, often demand frequent information exchange among D2D users, falling short of achieving global optimization. This paper introduces a framework comprising an outer loop and inner loop. In the outer loop, decentralized dynamic resource allocation optimization has been developed for self-organizing network communication aided by RIS. This is accomplished through the application of a multi-player multi-armed bandit approach, completing strategies for RIS and resource block selection. Notably, these strategies operate without requiring signal interaction during execution. Meanwhile, in the inner loop, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm has been adopted for cooperative learning with neural networks (NNs) to obtain optimal transmit power control and RIS phase shift control for multiple users, with a specified RIS and resource block selection policy from the outer loop. Through the utilization of optimization theory, distributed optimal resource allocation can be attained as the outer and inner reinforcement learning algorithms converge over time. Finally, a series of numerical simulations are presented to validate and illustrate the effectiveness of the proposed scheme.

An uplink multi-user tracking problem aided by multiple passive reconfigurable intelligent surfaces (RISs) is addressed in this work. Under a near-field circumstance, a multi-antenna base station (BS) localizes multiple moving single-antenna users by processing the received signals transmitted by users and reflected by RISs. Considering the users’ mobility and the potential obstruction of line-of-sight paths, a multi-user tracking system based on the extended Kalman filter (EKF) which fully exploits the temporal correlations between each user’s coordinate changes is designed. Then, the Bayesian Cramér–Rao bound (BCRB) of tracking errors is derived in a pattern consistent with the EKF process. Subsequently, an optimization scheme for passive phase shift design at the RISs is devised by minimizing the derived BCRB and is solved using the Gradient Descent method. Numerical results indicate that the accuracy of our tracking algorithm can approach the BCRB. With abundant RISs deployed and optimized, high-precision multi-user tracking via a single BS can be realized even in harsh localization environments.

In this study, a reconfigurable intelligent surface (RIS)-assisted wireless-powered mobile edge computing (WP-MEC) system is proposed, where a single-antenna unmanned aerial vehicle (UAV)-mounted cloudlet provides offloading opportunities to K user equipments (UEs) with a single antenna, and the K UEs can harvest the energy from the broadcast radio-frequency signals of the UAV. In addition, rate-splitting multiple access is used to provide offloading opportunities to multiple UEs for effective power control and high spectral efficiency. The aim of this paper is to minimize the total energy consumption by jointly optimizing the resource allocation in terms of time, power, computing frequency, and task load, along with the UAV trajectory and RIS phase-shift matrix. Since coupling issues between optimization variable designs are caused, however, an alternating optimization-based algorithm is developed. The performance of the proposed algorithm is verified via simulations and compared with the benchmark schemes of partial optimizations of resource allocation, path planning, and RIS phase design. The proposed algorithm exhibits high performance in WP-MEC systems with insufficient resources, e.g., achieving up to 40% energy reduction for a UAV with eight elements of RIS.

Reconfigurable intelligent surfaces (RISs) offer the potential to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must be jointly designed with conventional communication resources, such as beamformers, the transmit power, and computation time. However, due to the unique constraints on the phase shifts and the massive numbers of reflecting units and users in large-scale networks, the resulting optimization problems are challenging to solve. This paper provides a review of the current optimization methods and artificial-intelligence-based methods for handling the constraints imposed by RISs and compares them in terms of the solution quality and computational complexity. Future challenges in phase-shift optimization involving RISs are also described, and potential solutions are discussed.

Reconfigurable intelligent surfaces (RIS) aim to direct the incoming signal with adjustable phase shift using too many low-cost passive elements. In this paper, we investigate the scenario in which the UAV equipped with RIS acts as a reflective relay in order to prevent obstacles between the groundbased command and control system and another aerial vehicle to ensure uninterrupted communication. Channel modeling of the RIS supported UAV communication network is designed with double Weibull fading and the outage probability of proposed system is analyzed by presenting closed form expressions. Performance of the communication network according to the position parameters of the UAV and the number of RIS reflective surface elements is investigated using Monte-Carlo simulations. Furthermore, the presented scheme is compared with traditional cooperative communication systems (amplify-and-forward, decode-andforward). The obtained results showed that coverage of the proposed RIS-UAV supported architecture is improved efficiently and the RISUAV scheme is a rewarding candidate for the future communication networks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel algorithm for energy-efficient low-latency dynamic mobile edge computing (MEC), in the context of beyond 5G networks endowed with reconfigurable intelligent surfaces (RISs). We consider a scenario where new computing requests are continuously generated by a set of devices and are handled through a dynamic queueing system. Building on stochastic optimization tools, we devise a dynamic learning algorithm that jointly optimizes the allocation of radio resources (i.e., power, transmission rates, sleep mode and duty cycle), computation resources (i.e., CPU cycles), and RIS reflectivity parameters (i.e., phase shifts), while guaranteeing a target performance in terms of average end-to-end delay. The proposed strategy enables dynamic control of the system, performing a low-complexity optimization on a per-slot basis while dealing with time-varying radio channels and task arrivals, whose statistics are unknown. The presence and optimization of RISs helps boosting the performance of dynamic MEC, thanks to the capability to shape and adapt the wireless propagation environment. Numerical results assess the performance in terms of service delay, learning, and adaptation capabilities of the proposed strategy for RIS-empowered MEC. [ABSTRACT FROM AUTHOR]

Intelligent metasurfaces have gained significant importance in recent years due to their ability to dynamically manipulate electromagnetic (EM) waves. Their multifunctional characteristics, realized by incorporating active elements into the metasurface designs, have huge potential in numerous novel devices and exciting applications. In this article, recent progress in the field of intelligent metasurfaces are reviewed, focusing particularly on tuning mechanisms, hardware designs, and applications. Reconfigurable and programmable metasurfaces, classified as space gradient, time modulated, and space–time modulated metasurfaces, are discussed. Then, reconfigurable intelligent surfaces (RISs) that can alter their wireless environments, and are considered as a promising technology for sixth‐generation communication networks, are explored. Next, the recent progress made in simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR‐RISs) that can achieve full‐space EM wave control are summarized. Finally, the perspective on the challenges and future directions of intelligent metasurfaces are presented. [ABSTRACT FROM AUTHOR]

To assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has been envisioned as one of the promising solutions for enhancing signal transmissions in high-speed communications (HSC). In this paper, we present a time-varying channel model with distance-dependent Rician factors for the RIS-assisted HSC. Our model not only contains Rayleigh components and Doppler shift (DS) terms but also distance-dependent Rician factors, for characterizing time-varying features. In particular, we show that when the vehicle is far from the base station and the RIS, the channel contains only Rayleigh fading. However, when they are close enough, the channel can be considered as a light-of-sight channel. Based on the proposed model, it is proven that using RIS phase shift optimization, the DS of the cascaded links can be aligned with the DS of the direct link; and if the direct link is blocked, the DS can be removed entirely. Furthermore, we derive the closed-form expressions for the ergodic spectral efficiency and the outage probability of the proposed system. Besides, it is observed that the deployment strategy also affects the system performance. Simulation results validate all analyses. [ABSTRACT FROM AUTHOR]

Summary: The continuous growth of wireless connectivity and the emergence of the concept of the Internet of Everything in the future sixth‐generation (6G) network require a new communication paradigm. Different from the prior works that focus on performance optimization for communication networks, in this paper, we attempt to analyze the energy efficiency of unmanned aerial vehicles (UAVs) communication aided by reconfigurable intelligent surfaces (RIS) which is a new disruptive technology, for the reason that UAV has the line‐of‐sight (LoS) link transmission and flexibility and RIS has the low power for improving the communication reliability and network coverage. At firstly, when central limit theorem (CLT) assumption is used and the number of RIS reflecting elements is large, we derive the closed‐form expression of the average signal‐to‐interference‐plus‐noise ratio (SINR) of each user based on the new BS‐RIS‐user communication link and RIS‐user/BS association. Following this, we further gain the energy efficiency (EE) in closed‐form based on random access between BS and user. Finally, we further show the performance of EE under certain assumptions. In particular, the offered results demonstrate that the use of the RIS can significantly improve EE due to RIS assist in improving the SINR and has very low transmission power; meanwhile, the UAV equipped with RIS can also improve EE for the reason that RIS can be used as a mobile relay to take advantage of the LoS link transmission. [ABSTRACT FROM AUTHOR]

In the domain of wireless communication, the demand for high-speed data communication is at an all-time high as a result of proliferation of data intensive applications. Users not only demand for reliability in communication, high data-rates, enhanced security and high bandwidth, they also want their communication networks to be ubiquitous, wherein they can access their desired information from any device and at any location. These growing demands have led to continuous redesign of modern-day wireless communication architecture. This paper therefore proposes a technique for enhancing wireless communication through the design of an intelligent and reprogrammable wireless communication environment (WCE), using reconfigurable intelligent surfaces (RIS) trained by carefully-tuned deep-learning algorithms. This work shows that this technique is a viable solution for combating the effect of fading, interference and obstructions that have hitherto degraded the performance of most wireless communication systems. [ABSTRACT FROM AUTHOR]

This letter investigates a reconfigurable intelligent surface (RIS)-aided multiple-input-single-output (MISO) communication system which uses rate-splitting multiple access (RSMA) protocol. A multi-antenna base-station (BS) communicates with $K$ cell-edge users using RSMA protocol. Each user is assisted with a dedicated RIS. The closed-form expression for the outage probability (OP) is derived considering the discrete and optimal phase-shifts introduced by RIS elements. The interdependent constraints of the threshold and the RSMA factors are derived and analyzed. For getting further insights, the expression for asymptotic OP is derived. Furthermore, the effects of various factors such as number of RIS elements, number of quantization bits, RSMA factors, threshold, etc. are discussed. The correctness of the derived expressions is validated using the Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

We introduce a phase hopping scheme for reconfigurable intelligent surfaces (RISs) in which the phases of the individual RIS elements are randomly varied with each transmitted symbol. This effectively converts slow fading into fast fading. We show how this can be leveraged to significantly improve the outage performance especially for small outage probabilities without channel state information (CSI) at the transmitter and RIS. Furthermore, the same result can be accomplished even if only two possible phase values are available. Since we do not require perfect CSI at the transmitter or RIS, the proposed scheme has no additional communication overhead for adjusting the phases. This enables robust ultra-reliable communications with a reduced effort for channel estimation. [ABSTRACT FROM AUTHOR]

We consider a downlink multi-user scenario and investigate the use of reconfigurable intelligent surfaces (RISs) to maximize the dirty-paper-coding (DPC) sum rate of the RIS-assisted broadcast channel. Different from prior works, which maximize the rate achievable by linear precoders, we assume a capacity-achieving DPC scheme is employed at the transmitter and optimize the transmit covariances and RIS reflection coefficients to directly maximize the sum capacity of the broadcast channel. We propose an optimization algorithm that iteratively alternates between optimizing the transmit covariances using convex optimization and the RIS reflection coefficients using Riemannian manifold optimization. Our results show that the proposed technique can be used to effectively improve the sum capacity in a variety of scenarios compared to benchmark schemes.

The demanding objectives for the future sixth generation (6G) of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity, as well as revolutionary communication and computing paradigms. Among the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces (RISs), which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of functionalities. Incorporating RISs in wireless networks have been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one, intended for various networking objectives, such as coverage extension and capacity boosting, spatiotemporal focusing with benefits in energy efficiency and secrecy, and low electromagnetic field exposure. Motivated by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments, in this paper, we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal propagation. We also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems, which constitute a prerequisite step for the optimized incorporation of RISs in future wireless networks. Finally, we discuss the relevance of the RIS technology in the latest wireless communication standards, and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches.

Reconfigurable Intelligent Surfaces (RISs) are a class of metamaterials that have gained significant attention in recent years due to their potential to revolutionize wireless communication, sensing, and imaging technologies. RISs consist of a planar array of closely spaced, subwavelengthsized elements that can manipulate electromagnetic waves in a controllable manner. By reconfiguring the geometry, material properties, or phases of the individual elements on the RIS, the surface can be customized to meet specific application requirements. RISs can improve wireless communication by creating virtual channels, reducing interference, and improving overall quality. They can also enhance the efficiency of energy harvesting systems and improve sensing and imaging technologies by manipulating the propagation and scattering of electromagnetic waves. Additionally, RISs could be used to increase privacy and security by selectively blocking or allowing specific frequencies of electromagnetic waves. In this editorial, we provide a brief history of the development of RISs and discuss the design and fabrication of RIS structures. We also discuss RIS technology’s potential applications and benefits, including improved wireless communication, enhanced energy efficiency, advanced sensing and imaging, and increased privacy and security. Finally, we highlight some current research challenges and future directions for RIS technology. Overall, RISs hold great promise for advancing a wide range of technologies and applications, and we expect to see many exciting developments in this area.

In this paper, we propose a reconfigurable intelligent surface (RIS) that can dynamically switch the transmission and reflection phase of incident electromagnetic waves in real time to realize the dual-beam or quad-beam and convert the polarization of the transmitted beam. Such surfaces can redirect a wireless signal at will to establish robust connectivity when the designated line-of-sight channel is disturbed, thereby enhancing the performance of wireless communication systems by creating an intelligent radio environment. When integrated with a sensing element, they are integral to performing joint detection and communication functions in future wireless sensor networks. In this work, we first analyze the scattering performance of a reconfigurable unit element and then design a RIS. The dynamic field scattering manipulation capability of the RIS is validated by full-wave electromagnetic simulations to realize six different functions. The scattering characteristics of the proposed unit element, which incorporates two p-i-n diodes have been substantiated through practical implementation. This involved the construction of a simple prototype and the subsequent examination of its scattering properties via the free-space measurement method. The obtained transmission and reflection coefficients from the measurements are in agreement with the anticipated outcomes from simulations.

Reconfigurable intelligent surfaces (RISs) have promising coverage and data-rate gains for wireless communication systems in 5G and beyond. Prior work has mainly focused on analyzing the performance of these surfaces using simulations or lab-level prototypes. To draw accurate insights about the actual performance of these systems, this paper develops an RIS proof-of-concept prototype and extensively evaluates its potential gains in the field under realistic wireless communication settings. In particular, a 160-element RIS, operating at a 5.8 GHz band, is designed, fabricated, and accurately measured in the anechoic chamber. This surface is then integrated into a wireless communication system and the beamforming gains, pathloss, and coverage improvements are evaluated in realistic outdoor communication scenarios. When both the transmitter and receiver employ directional antennas, the developed RIS achieves 15–20 dB gain in the signal-to-noise ratio (SNR) in a range of ±60° beamforming angles. In terms of coverage, and considering a far-field experiment with a blockage between a basestation and a grid of mobile users and with an average signal path of 35 m, the RIS provides an average SNR improvement of 6 dB (max 8 dB) within an area > 75 m2. Thanks to the scalable RIS design, these SNR gains can be directly increased with larger RIS areas. For example, a single 1,600-element RIS with the same design is expected to provide 26 dB SNR gain for a similar deployment (theoretical estimation). These results draw useful insights into the design and performance of RIS systems and provide an important proof for their potential gains in real-world far-field wireless communication environments.

Reconfigurable intelligent surface (RIS) has recently been envisioned to provide an adaptable channel for futuristic wireless communication networks. This work characterized the impact of hardware impairments in the downlink RIS-aided non-orthogonal multiple access (NOMA) wireless networks. We considered the hardware impairments in the transceivers of the base station (BS) and users, phase error at the RIS and the imperfect successive interference cancellation (SIC) for the NOMA users. Specifically, the performance is evaluated by deriving the closed-form expressions for the outage probability (OP), spectral efficiency (SE) and energy efficiency (EE). Additionally, the performance of the orthogonal multiple access (OMA) system is also evaluated and compared with its NOMA counterpart. The RIS-aided NOMA outperforms OMA for the ideal hardware scenario. However, the hardware impairments significantly deteriorate RIS-aided NOMA's performance compared to RIS-aided OMA. Further, we have also compared the proposed RIS-aided NOMA with the baseline full-duplex relaying (FDR) based NOMA. The results show that the gains are more significant for a RIS-aided system than FDR.

New device capabilities supporting spectrum and energy-efficient internet of things (IoT) deployments are expected to drive the evolution of fifth-generation (5G) and beyond networks. Due to operating on the same spectrum of resources, every IoT pair interferes with each other. This paper utilizes reconfigurable intelligent surfaces (RISs) to mitigate inter-node interference in an IoT network through directional beamforming by adjusting the phase shifts of the passive elements of the RIS. We consider an RIS-assisted IoT network consisting of multiple pairs of IoT devices that utilize both direct paths and one-hop reflected paths. Two resource allocation problems, namely spectrum-efficiency maximization (SEM) and energy-efficiency maximization (EEM), are studied. Since the formulated optimization problems are non-convex in nature, we divide them into two sub-problems and solve them alternately. To obtain the optimal phase shifts of the elements of the RIS for both SEM and EEM, we extend the conjugate gradient technique to Riemannian manifolds. On the other hand, to obtain the optimal transmit power, we solve the transmit power allocation sub-problem as a difference of concave functions for the SEM and use a pricing-based technique for the EEM. Numerical results validate the effectiveness of deploying RISs to assist IoT networks, albeit concerning the RIS’s location, its number of elements, and the number of IoT node pairs. In particular, considerable spectrum and energy efficiency gains are achieved in comparison to baseline state-of-the-art networks.

The heterogeneity of optical wireless networks (OWNs) has expanded over decades in terms of services, node densities, mobility requirements, bandwidth needs, responsiveness, and physical device profile. Consequently, incorporating dynamic reconfigurability into future OWNs can satisfy their diverse realm of objectives. Towards this end, we provide our vision for the potential gains of integrating tunable optical elements in OWNs reflected in energy consumption reduction, coverage customization, data transfer rate boosting, highly accommodating multiple access schemes, enhancing physical layer security, supporting simultaneous services, and interference reduction. Finally, we speculate a roadmap for future research directions in tunable optics aided OWNs and the associated challenges with their deployment and operation.

To increase constantly the achievable rate of reconfigurable intelligent surfaces (RISs)-assisted communication systems, the traditional approaches are to deploy a few active elements randomly on the passive RISs. However, the effect of the geometry distribution of the deployment of the active elements is ignored in performance analysis. In this article, three types of geometry distribution with active elements on RISs, denoted as random distribution, uniform distribution, and eight-queens distribution, are discussed to analyze the affect on achievable rate in RISs-assisted wireless communications. Specifically, the optimal achievable rate is obtained according to the predefined codebook, and the codebook is determined by the reflection beamforming codeword related to the active elements geometry distribution in RISs. Simulation results show that different geometry distribution of active elements in RISs causes different influences to achievable rates. The eight-queens distribution proposed in this article for active elements in RISs brings the highest achievable rate compared with random distribution and uniform distribution. In the passive RISs surface, the distribution of a few active elements is limited by the eight-queens, further enhancing the achievable rate of the wireless communication system. This method has a 7% improvement over the conventional method.

Abstract The future sixth generation (6G) is going to face the significant challenges of massive connections and green communication. Recently, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) have been proposed as two key technologies to solve the above problems. Motivated by this fact, we consider a downlink RIS-aided NOMA system, where the source aims to communicate with the two NOMA users via RIS. Considering future network supporting real-time service, we investigate the system performance with the view of effective capacity (EC), which is an important evaluation metric of delay sensitive systems. Specifically, we derive the analytical expressions of the EC of the near and far users. To obtain more useful insights, we deduce the analytical approximation expressions of the EC in the low signal-to-noise-ratio approximation by utilizing Taylor expansion. Moreover, we provide the results of orthogonal multiple access (OMA) for the purpose of comparison. It is found that (1) The number of RIS components and the transmission power of the source have important effects on the performance of the considered system; (2) Compared with OMA, NOMA system has higher EC due to the short transmission time.

Abstract Intelligent metasurfaces have gained significant importance in recent years due to their ability to dynamically manipulate electromagnetic (EM) waves. Their multifunctional characteristics, realized by incorporating active elements into the metasurface designs, have huge potential in numerous novel devices and exciting applications. In this article, recent progress in the field of intelligent metasurfaces are reviewed, focusing particularly on tuning mechanisms, hardware designs, and applications. Reconfigurable and programmable metasurfaces, classified as space gradient, time modulated, and space–time modulated metasurfaces, are discussed. Then, reconfigurable intelligent surfaces (RISs) that can alter their wireless environments, and are considered as a promising technology for sixth‐generation communication networks, are explored. Next, the recent progress made in simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR‐RISs) that can achieve full‐space EM wave control are summarized. Finally, the perspective on the challenges and future directions of intelligent metasurfaces are presented.

A new method for the synthesis of single-bit reconfigurable passive electromagnetic skins (1RP-EMSs) featuring advanced beam shaping capabilities is proposed. By using single-bit unit cells, the multiscale problem of controlling 1RP-EMSs is formulated as a two-phase process. First, the macroscale synthesis of the discrete surface current that radiates the electromagnetic (EM) field fitting the user-designed requirements is performed by means of an innovative quantized version of the iterative projection method (QIPM). Subsequently, the meta-atom states of the 1RP-EMS are optimized with a customized implementation of the System-by-Design paradigm to yield a 1RP-EMS that supports such a feasible reference current. A representative set of numerical results is reported to assess the effectiveness of the proposed approach in designing and controlling single-bit meta-atom RP-EMSs that enable complex wave manipulations. [ABSTRACT FROM AUTHOR]

In this letter, we propose using a reconfigurable intelligent surface (RIS) to improve the performance of integrated sensing and communication (ISAC) systems since it can customize the wireless propagation environment by tuning phase shifts. However, it is not straightforward to integrate the RIS into ISAC systems. As the waveform design for the ISAC system is highly dependent on the channel conditions, the phase shift design of the RIS is fully coupled with the waveform design at the base station (BS). To address this challenge, we jointly optimize the beamformer at the BS and the phase shifts at the RIS in order to maximize the communication data rate and the mutual information (MI) for sensing, and then develop an efficient algorithm to solve this problem. Simulation results show that the proposed algorithm can effectively improve both sensing and communication performance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The evolution of Internet of Things (IoT) networks has been studied owing to the associated benefits in useful applications. Although the evolution is highly helpful, the increasing day-to-day demands of mobile users have led to immense requirements for further performance improvements such as efficient spectrum utilization, massive device connectivity, and high data rates. Fortunately, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) techniques have recently been introduced as two possible current-generation emerging technologies with immense potential of addressing the above-mentioned issues. In this paper, we propose the integration of RIS to the existing techniques (i.e., NOMA and relaying) to further enhance the performance for mobile users. We focus on a performance analysis of two-user group by exploiting two main performance metrics including outage probability and ergodic capacity. We provide closed-form expressions for both performance metrics to highlight how NOMA-aided RIS systems provide more benefits compared with the benchmark based on traditional orthogonal multiple access (OMA). Monte-Carlo simulations are performed to validate the correctness of obtained expressions. The simulations show that power allocation factors assigned to two users play a major role in the formation of a performance gap among two users rather than the setting of RIS. In particular, the strong user achieves optimal outage behavior when it is allocated 35% transmit power. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for millimeter wave (mmWave) networks. In this paper, we utilize tools from stochastic geometry to study the performance of a RIS-assisted mmWave cellular network. Specifically, the locations of the base stations (BSs) and the midpoints of the blockage are modeled as two independent Poisson point processes (PPPs), where the blockages are modeled by a Boolean model and a fraction of the blockages are coated with RISs. The particular characteristics of mmWave communications, i.e., directional beamforming and different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation, are incorporated into our analysis. We derive analytical expressions for the success probability and the area spectral efficiency. The success probability under the special case where the blockage parameter is sufficiently small is also derived. Numerical results demonstrate that better coverage performance and higher energy efficiency can be achieved by a large-scale deployment of RISs. In addition, the tradeoff between the BS and RIS densities is investigated and the results show that the RISs can indeed enable the traditional networks to improve the success probability, especially for the cell-edge region, with limited power consumption. [ABSTRACT FROM AUTHOR]

The emerging technology of reconfigurable intelligent surfaces (RISs) is provisioned as an enabler of smart wireless environments, offering a highly scalable, low-cost, hardware-efficient, and almost energy-neutral solution for dynamic control of the propagation of electromagnetic signals over the wireless medium, ultimately providing increased environmental intelligence for diverse operation objectives. One of the major challenges with the envisioned dense deployment of RISs in such reconfigurable radio environments is the efficient configuration of multiple metasurfaces with limited, or even the absence of, computing hardware. In this article, we consider multiuser and multi-RIS-empowered wireless systems and present a thorough survey of the online machine learning approaches for the orchestration of their various tunable components. Focusing on the sum-rate maximization as a representative design objective, we present a comprehensive problem formulation based on deep reinforcement learning (DRL). We detail the correspondences among the parameters of the wireless system and the DRL terminology, and devise generic algorithmic steps for the artificial neural network training and deployment while discussing their implementation details. Further practical considerations for multi-RIS-empowered wireless communications in the sixth-generation (6G) era are presented along with some key open research challenges. Different from the DRL-based status quo, we leverage the independence between the configuration of the system design parameters and the future states of the wireless environment, and present efficient multiarmed bandits approaches, whose resulting sum-rate performances are numerically shown to outperform random configurations, while being sufficiently close to the conventional deep $Q$ network (DQN) algorithm, but with lower implementation complexity. [ABSTRACT FROM AUTHOR]

For all of the tumultuous revolutions in wireless technology over the past several decades, there have been a couple of constants. One is the overcrowding of radio bands, and the other are attempts to escape that congestion by exploiting higher and higher frequencies. And today, as engineers roll out 5G and plan for 6G wireless, they find themselves at a crossroads. [ABSTRACT FROM AUTHOR]

A reconfigurable intelligent surface (RIS) is a planar structure that is engineered to dynamically control the electromagnetic waves. In wireless communications, RISs have recently emerged as a promising technology for realizing programmable and reconfigurable wireless propagation environments through nearly passive signal transformations. With the aid of RISs, a wireless environment becomes part of the network design parameters that are subject to optimization. In this tutorial article, we focus our attention on communication models for RISs. First, we review the communication models that are most often employed in wireless communications and networks for analyzing and optimizing RISs and elaborate on their advantages and limitations. Then, we concentrate on models for RISs that are based on inhomogeneous sheets of surface impedance and offer a step-by-step tutorial on formulating electromagnetically consistent analytical models for optimizing the surface impedance. The differences between local and global designs are discussed and analytically formulated in terms of surface power efficiency and reradiated power flux through the Poynting vector. Finally, with the aid of numerical results, we discuss how approximate global designs can be realized by using locally passive RISs with zero electrical resistance (i.e., inhomogeneous reactance boundaries with no local power amplification) even for large angles of reflection and at high power efficiency. [ABSTRACT FROM AUTHOR]

Wireless connectivity is regarded as a fundamental need for our society. Between 2020 and 2030, it is forecast that the data traffic of the global internet protocol will increase by 55% each year, eventually reaching 5016 EB, with data rates scaling up to 1 Tb/s. Besides supporting very high data rates, future wireless networks are expected to offer several other heterogeneous services, which include sensing, localization, low-latency, and ultrareliable communications. Fifth-generation (5G) networks are, however, not designed to meet these requirements. As the demands and needs become more stringent, in fact, fundamental limitations arise, which are ultimately imposed by the inherent nature of the wireless operation. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are 2-D metasurfaces, which can intelligently manipulate electromagnetic waves by low-cost near passive reflecting elements. RIS is viewed as a potential key technology for the sixth-generation (6G) wireless communication systems mainly due to its advantages in tuning wireless signals, thus smartly controlling propagation environments. In this article, we aim at addressing channel characterization and modeling issues of RIS-assisted wireless communication systems. First, the concept, principle, and potential applications of RIS are given. An overview of RIS-based channel measurements and experiments is presented by classifying frequency bands, scenarios, system configurations, RIS constructions, experiment purposes, and channel observations. Then, RIS-based channel characteristics are studied, including reflection and transmission, the Doppler effect and multipath fading mitigation, channel reciprocity, channel hardening, rank improvement, far field, near field, and so on. RIS-based channel modeling works are investigated, including large-scale path loss models and small-scale multipath fading models. Finally, future research directions related to RIS-assisted channels are also discussed. [ABSTRACT FROM AUTHOR]

The term “metasurface” (MTS) denotes an artificial surface constituted by a distribution of electrically small elements that collectively exhibit equivalent homogeneous boundary conditions (BCs) to an interacting electromagnetic field. MTSs are becoming increasingly popular due to the technological simplification that they offer with respect to volumetric metamaterials. In this article, we review the basic theory behind microwave MTSs seen as reconfigurable intelligent surfaces (RISs), oriented to the future visionary challenge of a smart radio environment. To this end, two different typologies of MTS are reviewed: surface-wave-based MTSs and nonspecular reflective MTSs. Both types can be effectively characterized using simplified problems that locally match the homogenized, modulated BCs. A different use of these problems allows for an accurate design of radiated and scattered fields. An accurate ray representation is also suggested, which allows for an effective description of the scattered field also in the Fresnel region and for the insertion of the MTS description in ray-tracing tools for network planning. Several examples of practical implementation are shown, and the challenges in applying electronic reconfigurability are discussed. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are gaining huge momentum in the field of wireless communications due to the paradigm shift that they bring. Indeed, they allow making any environment electromagnetically smart and dynamically reconfigurable for more efficient and greener wireless communications. As physicists, we proposed to use electronically tunable metasurfaces to shape the electromagnetic waves carrying our wireless communications in reflection almost ten years ago, inspired by some works that we and colleagues did in the field of wave control in complex media. In this article, we review the seminal works that led us to propose this concept, starting from the original one that is time reversal. Then, we propose a physicist’s point of view of RISs using a comparison with phase conjugation. Finally, we highlight what we think are their limitations, relying on both our knowledge of wave control and our study of them over a decade. [ABSTRACT FROM AUTHOR]

In future cellular systems, wireless localization and sensing functions will be built-in for specific applications, e.g., navigation, transportation, and healthcare, and to support flexible and seamless connectivity. Driven by this trend, the need for fine-resolution sensing solutions and centimeter-level localization accuracy arises, while the accuracy of current wireless systems is limited by the quality of the propagation environment. Recently, with the development of new materials, reconfigurable intelligent surfaces (RISs) provide an opportunity to reshape and control the electromagnetic characteristics of the environment, which can be utilized to improve the performance of wireless sensing and localization. In this tutorial, we will first review the background and motivation for utilizing wireless signals for sensing and localization. Next, we will introduce how to incorporate RIS into applications of sensing and localization, including key challenges and enabling techniques, and then, some case studies will be presented. Finally, future research directions will also be discussed. [ABSTRACT FROM AUTHOR]

Optimally extracting the advantages available from reconfigurable intelligent surfaces (RISs) in wireless communications systems requires estimation of the channels to and from the RIS. The process of determining these channels is complicated when the RIS is composed of passive elements without any sensing or data processing capabilities, and thus, the channels must be estimated indirectly by a noncolocated device, typically a controlling base station (BS). In this article, we examine channel estimation for passive RIS-based systems from a fundamental viewpoint. We study various possible channel models and the identifiability of the models as a function of the available pilot data and behavior of the RIS during training. In particular, we will consider situations with and without line-of-sight propagation, single-antenna and multi-antenna configurations for the users and BS, correlated and sparse channel models, single-carrier and wideband orthogonal frequency-division multiplexing (OFDM) scenarios, availability of direct links between the users and BS, exploitation of prior information, as well as a number of other special cases. We further conduct simulations of representative algorithms and comparisons of their performance for various channel models using the relevant Cramér-Rao bounds. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) and nonorthogonal multiple access (NOMA) have been recognized as key enabling techniques for the envisioned sixth generation (6G) of mobile communication networks. The key feature of RISs is to intelligently reconfigure the wireless propagation environment, which was once considered to be fixed and untunable. The key idea of NOMA is to utilize users’ dynamic channel conditions to improve spectral efficiency and user fairness. Naturally, the two communication techniques are complementary to each other and can be integrated to cope with the challenging requirements envisioned for 6G mobile networks. This survey provides a comprehensive overview of the recent progress on the synergistic integration of RISs and NOMA. In particular, the basics of both techniques are introduced first, and then, the fundamentals of RIS-NOMA are discussed for two communication scenarios with different transceiver capabilities. Resource allocation is of paramount importance for the success of RIS-assisted NOMA networks, and various approaches, including artificial intelligence (AI)-empowered designs, are introduced. Security provisioning in RIS-NOMA networks is also discussed as wireless networks are prone to security attacks due to the nature of the shared wireless medium. Finally, the survey is concluded with detailed discussions of the challenges arising in the practical implementation of RIS-NOMA, future research directions, and emerging applications. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has emerged as a promising technique for wireless communication networks. By dynamically tuning the reflection amplitudes/phase shifts of a large number of passive elements, IRS enables flexible wireless channel control and configuration and thereby enhances the wireless signal transmission rate and reliability significantly. Despite the vast literature on designing and optimizing assorted IRS-aided wireless systems, prior works have mainly focused on enhancing wireless links with single signal reflection only by one or multiple IRSs, which may be insufficient to boost the wireless link capacity under some harsh propagation conditions (e.g., indoor environment with dense blockages/obstructions). This issue can be tackled by employing two or more IRSs to assist each wireless link and jointly exploiting their single as well as multiple signal reflections over them. However, the resultant double-/multi-IRS-aided wireless systems face more complex design issues as well as new practical challenges for implementation compared to the conventional single-IRS counterpart, in terms of IRS reflection optimization, channel acquisition, as well as IRS deployment and association/selection. As such, a new paradigm for designing multi-IRS cooperative passive beamforming and joint active/passive beam routing arises, which calls for innovative design approaches and optimization methods. In this article, we give a tutorial overview of multi-IRS-aided wireless networks, with an emphasis on addressing the new challenges due to multi-IRS signal reflection and routing. Moreover, we point out important directions worthy of research and investigation in the future. [ABSTRACT FROM AUTHOR]

With massive deployment, multiple-input–multiple-output (MIMO) systems continue to take mobile communications to new heights, but the ever-increasing demands mean that there is a need to look beyond MIMO and pursue the next disruptive wireless technologies. Reconfigurable intelligent surface (RIS) is widely considered a key candidate technology block to provide the next generational leap. The first part of this article provides an updated overview of the conventional reflection-based RIS technology, which complements the existing literature to include active and semiactive RIS, and the synergies with cell-free massive MIMO (CF mMIMO). Then, we widen the scope to discuss the surface-wave-assisted RIS that represents a different design dimension in utilizing metasurface technologies. This goes beyond being a passive reflector and can use the surface as an intelligent propagation medium for superb radio propagation efficiency. The third part of this article turns the attention to the fluid antenna, a novel antenna technology that enables a diverse form of reconfigurability that can combine with RIS for ultrahigh capacity, power efficiency, and scalability. This article concludes with a discussion of the potential synergies that can be exploited between MIMO, RIS, and fluid antennas. [ABSTRACT FROM AUTHOR]

Nonterrestrial communications have emerged as a key enabler for seamless connectivity in the upcoming generation networks. This kind of network can support high data rate communications among aerial platforms (i.e., unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and satellites) and cellular networks, achieving anywhere and anytime connections. However, there are many practical implementation limitations, especially overload power consumption, high probability of blockage, and dynamic propagation environment. Fortunately, the recent technology reconfigurable intelligent surface (RIS) is expected to be one of the most cost-efficient solutions to address such issues. RIS with low-cost elements can bypass blockages and create multiple line-of-sight (LoS) links and provide controllable communication channels. In this article, we present a comprehensive literature review on the RIS-assisted nonterrestrial networks (RANTNs). First, the framework of the RANTNs is introduced with detailed discussion about distinct properties of RIS in NTNs and the two deployment types of RIS, that is, terrestrial RISs (TRISs), and aerial RISs (ARISs), and the classification of RANTNs, including RIS-assisted air-to-ground (A2G)/ground-to-air (G2A), ARIS-assisted ground-to-ground (G2G), and RIS-assisted air-to-air (A2A) communications. In combination with next-generation communication technologies, the advanced technologies in RANTNs are discussed. Then, we overview the literature related to RANTNs from the perspectives of performance analysis and optimization, followed by the widely used methodologies. Finally, open challenges and future research direction in the context of the RANTNs are highlighted. [ABSTRACT FROM AUTHOR]

Programmable wireless environments (PWEs) utilize internetworked intelligent metasurfaces to transform wireless propagation into a software-controlled resource. In this article, the interplay is explored between the user devices, the metasurfaces, and the PWE control system from the theory to the end-to-end implementation. This article first discusses the metasurface hardware and software, covering the complete workflow from the user device initialization to its final service via the PWE. Furthermore, to be compatible with the 5G and 6G wireless systems, the software-defined networking (SDN) paradigm is extended to achieve scalable internetworking and central control in PWE deployments with multiple metasurfaces and multihop communication. Subsequently, the set of SDN foundations is exploited in order to abstract the physics behind PWEs and a theoretical framework is established to describe and manipulate them in an algorithmic form. This can lead to smart radio environments that are readily accessible from various engineering disciplines, facilitating their integration into existing networks, wireless systems, and applications. This article is concluded by outlining strategies for the optimal placement of metasurfaces within a PWE-controlled space, open challenges in PWE security, specialized SDN integration issues, and theoretical problems toward the graph-driven modeling of PWEs. [ABSTRACT FROM AUTHOR]