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## Abstract

Reconfigurable intelligent surfaces (RISs) are an emerging transmission technology for application to wireless communications. RISs can be realized in different ways, which include (i) large arrays of inexpensive antennas that are usually spaced half of the wavelength apart; and (ii) metamaterial-based planar or conformal large surfaces whose scattering elements have sizes and inter-distances much smaller than the wavelength. Compared with other transmission technologies, e.g., phased arrays, multi-antenna transmitters, and relays, RISs require the largest number of scattering elements, but each of them needs to be backed by the fewest and least costly components. Also, no power amplifiers are usually needed. For these reasons, RISs constitute a promising software-defined architecture that can be realized at reduced cost, size, weight, and power (C-SWaP design), and are regarded as an enabling technology for realizing the emerging concept of smart radio environments (SREs). In this paper, we (i) introduce the emerging research field of RIS-empowered SREs; (ii) overview the most suitable applications of RISs in wireless networks; (iii) present an electromagnetic-based communication-theoretic framework for analyzing and optimizing metamaterial-based RISs; (iv) provide a comprehensive overview of the current state of research; and (v) discuss the most important research issues to tackle. Owing to the interdisciplinary essence of RIS-empowered SREs, finally, we put forth the need of reconciling and reuniting C. E. Shannon’s mathematical theory of communication with G. Green’s and J. C. Maxwell’s mathematical theories of electromagnetism for appropriately modeling, analyzing, optimizing, and deploying future wireless networks empowered by RISs.

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... Over the past few years, intelligent reflecting surface (IRS) has emerged as a promising technology to achieve a smart wireless environment that allows enhanced coverage, security, and interference suppression [2][3][4]. An IRS comprises a large number of low-cost sub-wavelength passive meta-material elements, each of which is able to independently control the phase of the impinging signal and hence shape the radiation beampattern to alter the radio propagation environment [2,5,6]. ...
... Over the past few years, intelligent reflecting surface (IRS) has emerged as a promising technology to achieve a smart wireless environment that allows enhanced coverage, security, and interference suppression [2][3][4]. An IRS comprises a large number of low-cost sub-wavelength passive meta-material elements, each of which is able to independently control the phase of the impinging signal and hence shape the radiation beampattern to alter the radio propagation environment [2,5,6]. The near passive behavior implies potential for large-scale IRS deployment without additional energy consumption when compared with the conventional relays [7,8]. ...
... t (θt, f k ), G m,k = bm(θ d,im , f k )a T t (θ im , f k ),(17)andW m,k = bm(θt,i m , f k )b T m (θt,i m , f k ),where θi m , θt,i m and θ d,im denote the angle of m-th IRS with respect to DFBS,2 Herein, the complex-valued term e −j2πf D,1 τ d is omitted because f D,1 τ d = const./c 2 ≈ 0. ...
Preprint
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Intelligence reflecting surface (IRS) is recognized as the enabler of future dual-function radar-communications (DFRC) for improving spectral efficiency, coverage, parameter estimation, and interference suppression. Prior studies on IRS-aided DFRC focus on either narrowband processing, single-IRS deployment, static targets, non-clutter scenario, or under-utilized line-of-sight (LoS) and non-line-of-sight (NLoS) paths. In this paper, we address the aforementioned shortcomings by optimizing a wideband DFRC system that comprises multiple IRSs and a dual-function base station that jointly processes the LoS and NLoS wideband multi-carrier signals to extract communications symbols and moving target parameters in the presence of clutter. We formulate the transmit and IRS beamformer design as the maximization of the worst-case radar signal-to-interference-plus-noise ratio (SINR) subject to transmit power and communications SINR. We tackle this nonconvex problem under the alternating optimization framework, where the subproblems are solved by a combination of Dinkelbach algorithm, consensus alternating direction method of multipliers, and Riemannian steepest decent. Our numerical experiments show that the proposed multi-IRS-aided wideband DFRC provides over 6 dB radar SINR and 40% improvement in target detection over a single-IRS system.
... In the second, a more practical feasibility set is considered in which only the phase of each RIS component can be optimized, while the amplitude is fixed. This feasibility set can be referred to as the reflecting RIS [3]. In the third, we employ the model in [52] in which the amplitude is not constant, but it is a function of the phase of RIS components. ...
... This feasibility set provides a performance upper bound. In a more realistic feasibility set, often found in the literature, we can tune the phase of each reflecting coefficient continuously between 0 and 2π, while the amplitude is fixed to 1 [2], [3]. This feasibility set can be written as ...
... This case is also referred to as intelligent reflecting surface (IRS) to emphasize that there is only a passive phase-shifting beamforming at the intelligent surfaces [3]. Note that, in some studies such as [39], an attenuation factor for the reflecting coefficients is considered such that |θ mi | = η < 1. ...
Preprint
In this paper, we study the performance of reconfigurable intelligent surfaces (RISs) in a multicell broadcast channel (BC) that employs improper Gaussian signaling (IGS) jointly with non-orthogonal multiple access (NOMA) to optimize either the minimum-weighted rate or the energy efficiency (EE) of the network. We show that although the RIS can significantly improve the system performance, it cannot mitigate interference completely, so we have to employ other interference-management techniques to further improve performance. We show that the proposed NOMA-based IGS scheme can substantially outperform proper Gaussian signaling (PGS) and IGS schemes that treat interference as noise (TIN) in particular when the number of users per cell is larger than the number of base station (BS) antennas (referred to as overloaded networks). In other words, IGS and NOMA complement to each other as interference management techniques in multicell RIS-assisted BCs. Furthermore, we consider three different feasibility sets for the RIS components showing that even a RIS with a small number of elements provides considerable gains for all the feasibility sets.
... A reconfigurable intelligent surface (RIS), a metasurface with numerous low-cost reflectors, can inherently manipulate the propagation environment to enhance energy and spectrum efficiency [1], [2]. RIS can be passive or active. ...
... phase 1 . The system then adopts a codebook-based passive beamforming approach, where the RIS selects the best beam based on the received pilot sequences from the BS or users [1]. ...
... , e jθN ) is the reflectioncoefficients matrix at the RIS. With optimal RIS phase shifts, coherent combining at the user yields a high array gain proportional to N 2 , a fundamental motivation of employing RIS [1]. However, when the direct link between the BS and the user is strong enough, the array gain becomes marginal [2]. ...
Preprint
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Reconfigurable intelligent surface (RIS)-based communication networks promise to improve channel capacity and energy efficiency. However, the promised capacity gains could be negligible for passive RISs because of the double pathloss effect. Active RISs can overcome this issue because they have reflector elements with a low-cost amplifier. This letter studies the active RIS-aided simultaneous wireless information and power transfer (SWIPT) in a multiuser system. The users exploit power splitting (PS) to decode information and harvest energy simultaneously based on a realistic piecewise nonlinear energy harvesting model. The goal is to minimize the base station (BS) transmit power by optimizing its beamformers, PS ratios, and RIS phase shifts/amplification factors. The simulation results show significant improvements (e.g., 19% and 28%) with the maximum reflect power of 10 mW and 15 mW, respectively, compared to the passive RIS without higher computational complexity cost. We also show the robustness of the proposed algorithm against imperfect channel state information.
... Requirements for high data rates and heterogeneous services in future sixth-generation (6G) wireless networks bring challenges to system designs [1]- [3]. The smart radio environment (SRE) is envisioned to be a promising solution [3], [4]. ...
... Requirements for high data rates and heterogeneous services in future sixth-generation (6G) wireless networks bring challenges to system designs [1]- [3]. The smart radio environment (SRE) is envisioned to be a promising solution [3], [4]. Equipped with several low-cost reconfigurable elements and a smart controller, a reconfigurable intelligent surface (RIS) is capable of intelligently altering the phase of signals [3], [5], [6], hence the propagation of which is controllable and the SRE can be realized. ...
... The smart radio environment (SRE) is envisioned to be a promising solution [3], [4]. Equipped with several low-cost reconfigurable elements and a smart controller, a reconfigurable intelligent surface (RIS) is capable of intelligently altering the phase of signals [3], [5], [6], hence the propagation of which is controllable and the SRE can be realized. However, the main issue of conventional reflectingonly RISs in existing works is that user equipment (UE) can only receive reflected signals from base stations (BSs) located at the same side of the assisted RIS, which degrades the coverage performance especially for those blocked UEs. ...
Article
The simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that there exist optimal energy splitting coefficients of STAR-RISs to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located at different sides; 2) in low RIS density regions, STAR-RISs outperform conventional RISs while in dense regions the conclusion is opposite.
... In view of the recent researches on communication networks, the feasibility of intelligent reflecting surface (IRS) technology has been gradually verified [22,23], which can establish programmable radio wave propagation to reconfigure the wireless propagation environment [24]. There are some advantages of IRS: i) IRS can enrich the channel scattering conditions, enhance the system's multiplexing gain, and improve the received signal strength [25]; ii) Numerous experimental results have shown that IRS deployment can effectively improve wireless networks' throughput and coverage performance [26,27]. iii) Unlike the traditional active relay, IRS reflects signals in full-duplex mode through passive beamforming and does not impose additional energy consumption and noise [28]. ...
... Furthermore, IRS is deemed as a new transmission technology for future wireless networks, which consists of a large number of carefully designed arrangements of electromagnetic units, and the signal is controlled by changing the phase and amplitude of the unit [28]. There are some advantages of IRS: i) IRS can enrich the channel scattering conditions, enhance the system's multiplexing gain, and improve the received signal strength [25]; ii) Numerous experimental results have shown that IRS deployment can effectively improve wireless networks' throughput and coverage performance [26,27]. Inspired by the appealing advantages of IRS, we consider to utilize IRS in the NOMA-MEC networks to further improve the offloading outage behavior, system throughput and energy efficiency and to guarantee the quality of service requirements of MEC services. ...
... Remark 3. Upon substituting (25) and (26) into (18), the diversity order of the task x m is equal to P when Q = 1 and Q ≥ 2. ...
Article
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... In response to the above need, several researchers have recently focused their attention on combining UAVs and reconfigurable intelligent surfaces (RIS) [17], [18]. As a result of these efforts two system models have been developed. ...
... It is assumed that all the fading channels considered are independent, identical, slowly varying, and flat. This assumption has been considered in several published contributions, including [18], [47], [48], and it is based on the fact that the MAs are spaced sufficiently far apart that the mutual coupling can be ignored. As a result, they act as separate filters with a single input [49] 1 . ...
... Finally, by applying (18) in (36), we get (33). This concludes the proof. ...
Article
Full-text available
In this paper, we analyze the performance of a reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV) wireless system that is affected by mixture-gamma small-scale fading, stochastic disorientation and misalignment, as well as transceivers hardware imperfections. First, we statistically characterize the end-to-end channel for both cases, i.e., in the absence as well as in the presence of disorientation and mis-alignment, by extracting closed-form formulas for the probability density function (PDF) and the cumulative distribution function (CDF). Building on the aforementioned expressions, we extract novel closed-form expressions for the outage probability (OP) in the absence and the presence of disorientation and misalignment as well as hardware imperfections. In addition, high signal-to-noise ratio OP approximations are derived, leading to the extraction of the diversity order. Finally, an OP floor due to disorientation and misalignment is presented.
... Reconfigurable intelligent surfaces (RIS) provide an alternative solution to relays to reduce the impact of blockage in millimeter wave networks [1]. Extensive recent work has focused on designing strategies to configure a RIS under different metrics [2], or to estimate the corresponding composite channel [3]. ...
... The previous studies on RIS placement make certain simplify assumptions about the geometry. First, some work like [1]- [4], [6] neglects the elevation angle of the incident and reflected signals at the RIS. This results in neglecting the orientation dependent on the gain, and users might get lower rates than expected [9]. ...
Preprint
Millimeter wave (MmWave) systems are vulnerable to blockages, which cause signal drop and link outage. One solution is to deploy reconfigurable intelligent surfaces (RISs) to add a strong non-line-of-sight path from the transmitter to receiver. To achieve the best performance, the location of the deployed RIS should be optimized for a given site, considering the distribution of potential users and possible blockers. In this paper, we find the optimal location, height and downtilt of RIS working in a realistic vehicular scenario. Because of the proximity between the RIS and the vehicles, and the large electrical size of the RIS, we consider a 3D geometry including the elevation angle and near-field beamforming. We provide results on RIS configuration in terms of both coverage ratio and area-averaged rate. We find that the optimized RIS improves the average averaged rate fifty percent over the case without a RIS, as well as further improvements in the coverage ratio.
... However, when the direct links to the UEs or targets are weak or absent, the aforementioned methods [10]- [12] will not be able to provide desired levels of radar or communication performance. To combat such harsh propagation environments, an emerging technology with large two-dimensional array of passive reflectors, referred to as reconfigurable intelligent surfaces (RISs) is receiving significant attention, separately for wireless communications [14], [15], localization [16], and radar sensing [17]- [20]. ...
... Throughout the simulations, we model the DFBS as a ULA with M = 16 half-wavelength spaced elements. Both the comm-and radar-RISs are modeled as URAs comprising of quarter-wavelength spaced elements [15]. We model the entries of the channels H br , G br , and h H ru,k for k = 1, . . . ...
Preprint
We consider transmit beamforming and reflection pattern design in reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) systems to jointly precode communication symbols and radar waveforms. We treat two settings of multiple users and targets. In the first, we use a single RIS to enhance the communication performance of the ISAC system and design beams with good cross-correlation properties to match a desired beam pattern while guaranteeing a desired signal-to-interference plus noise ratio (SINR) for each user. In the second setting, we use two dedicated RISs to aid the ISAC system, wherein the beams are designed to maximize the worst-case target illumination power while guaranteeing a desired SINR for each user. We propose solvers based on alternating optimization as the design problems in both cases are non-convex optimization problems. Through a number of numerical simulations, we demonstrate the advantages of RIS-assisted ISAC systems. In particular, we show that the proposed single-RIS assisted ISAC system improves the minimum user SINR while suffering from a moderate loss in radar target illumination power. On the other hand, the dual-RIS assisted ISAC system improves both minimum user SINR as well as worst-case target illumination power at the targets, especially when the users and targets are not directly visible.
... The demand is expected to continuously grow in the upcoming sixth-generation (6G) cellular systems, resulting from new applications and services [1]. Intelligent reflecting surface (IRS) has been identified as an appealing complementary technology to latest multipleinput multiple-output (MIMO) techniques, to improve spectral and energy efficiency and increase data rates [2], [3]. An IRS is a two-dimensional meta-surface array, which can induce favorable scattering to create anomalous reflection and programmable wireless channels via adjusting the phase-shifts of the IRS [4]. ...
... For each particle θ (0) p , evaluate the fitness value of each particle using (36), and obtain the initial best position set {θp} P p=1 ; 3 Find the global optimal position θ = arg minθ{J (0) (θ1), J (0) (θ2), · · · , J (0) (θP )}; 4 end 5 Step 2: Iterative search 6 for i = 1 : Iiter do 7 Update particle velocity {v the BS runs the water-filling algorithm to allocate the transmit powers for the data streams in the next time slot, as described in Sec. III-A. ...
Preprint
Full-text available
The application of intelligent reflecting surface (IRS) depends on the knowledge of channel state information (CSI), and has been hindered by the heavy overhead of channel training, estimation, and feedback in fast-changing channels. This paper presents a new two-timescale beamforming approach to maximizing the average achievable rate (AAR) of IRS-assisted MIMO systems, where the IRS is configured relatively infrequently based on statistical CSI (S-CSI) and the base station precoder and power allocation are updated frequently based on quickly outdated instantaneous CSI (I-CSI). The key idea is that we first reveal the optimal small-timescale power allocation based on outdated I-CSI yields a water-filling structure. Given the optimal power allocation, a new mini-batch sampling (mbs)- based particle swarm optimization (PSO) algorithm is developed to optimize the large-timescale IRS configuration with reduced channel samples. Another important aspect is that we develop a model-driven PSO algorithm to optimize the IRS configuration, which maximizes a lower bound of the AAR by only using the S-CSI and eliminates the need of channel samples. The modeldriven PSO serves as a dependable lower bound for the mbs-PSO. Simulations corroborate the superiority of the new two-timescale beamforming strategy to its alternatives in terms of the AAR and efficiency, with the benefits of the IRS demonstrated.
... Reconfigurable intelligent surface (RIS) is a promising technology, enabling a smart radio environment (SRE) to meet the challenges of sixth-generation (6G) wireless networks [1]. It consists of a number of low-cost nearly passive elements that can modify the phase shifts and even the amplitude of the impinging signals to realize an SRE through a backhaul controller. ...
... Especially, the transmitted (t) and reflected (r) signals by the nth element can be modelled as t n = ( β t n e jφ t n )s n and r n = ( β r n e jφ r n )s n , respectively, where β k n ∈ [0, 1] and φ k n ∈ [0, 2π) express the independent amplitude and phase-shift response of the nth element, and k ∈ {t, r} corresponds to the UE found in the transmission (t) or reflection (r) region [11]. 1 Note that the choice of φ t n and φ r n is independent from each other, but the amplitude adjustments are correlated based on the law of energy conservation as β t n + β r n = 1, ∀n ∈ N . ...
Preprint
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In this paper, we investigate a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisting a massive multiple-input multiple-output (mMIMO) system. In particular, we derive a closed-form expression for the coverage probability of a STAR-RIS assisted mMIMO system while accounting for correlated fading and phase-shift errors. Notably, the phase configuration takes place at every several coherence intervals by optimizing the coverage probability since the latter depends on statistical channel state information (CSI) in terms of large-scale statistics. As a result, we achieve a reduced complexity and overhead for the optimization of passive beamforming, which are increased in the case of STAR-RIS networks with instantaneous CSI. Numerical results corroborate our analysis, shed light on interesting properties such as the impact of the number of RIS elements and the effect of phase errors, along with affirming the superiority of STAR-RIS against reflective-only RIS.
... Each reflecting unit is controllable, and thus it can reflect and focus the impinging signals in a desired direction in a nearly passive way. Thus, RIS are an energy-efficient alternative to active antenna architecture such as relays [4], [5]. However, the deployment of RIS in terrestrial networks involves several challenges, including inflexible deployment and weak wireless channel conditions due to shadowing, blockages and NLoS links. ...
... Despite being passive in nature, the RIS units consume energy for control and configuration [4], [5]. The energy consumption might be significant for HAPS equipped with a large number of reflectors. ...
Preprint
p> The ever-increasing number of users and new services in urban regions can lead terrestrial base stations (BSs) to become overloaded and, consequently, some users to go unserved. Compounding this, users in urban areas can face severe shadowing and blockages, which means that some users do not receive a desired quality of service (QoS). Motivated by the energy and cost benefits of reconfigurable intelligent surfaces (RIS) and the advantages of high altitude platform stations (HAPS), including their wide footprint and strong line-of-sight (LoS) links, we propose a solution to service the stranded users using the RISaided HAPS. More specifically, we propose to service the stranded users by a dedicated control station (CS) via a HAPS equipped with RIS (HAPS-RIS). Through this approach, users are not restricted from being serviced by the cell they belong to; hence, we refer to this approach as beyond-cell communication. As we demonstrate in this paper, beyond-cell communication works in tandem with legacy terrestrial networks to support uncovered or unserved users. Optimal transmit power and RIS unit assignment strategies for the users based on different network objectives are introduced. Numerical results demonstrate the benefits of the proposed beyond-cell communication approach. Moreover, the results provide insights into the different optimization objectives and their interplay with minimum quality-of-service (QoS) and network resources, such as transmit power and the number of reflectors. </p
... Even though RSMA has numerous benefits, establishing reliable communication links through fast-varying wireless channels continues to be a challenge. As an attempt to overcome channel issues, a promising technology called an intelligent reflecting surface (IRS) has been proposed [3]. An IRS can be seen as a cluster of controllable scatterers, where each scatterer, i.e., a reflecting element, can be configured independently to generate distinct amplitude and phase responses. ...
... The reflecting elements, made of passive conductive materials, are tuned by a low-power control layer, which can be implemented through diverse technologies. Existing designs propose the use of PIN diodes, varactors, graphene, and liquid crystal-based solutions [3]. Moreover, the reflecting elements usually have dimensions much smaller than the carrier wavelength [9]. ...
Preprint
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Rate-splitting multiple access (RSMA) has recently appeared as a powerful technique for improving the downlink performance of multiple-input multiple-output (MIMO) systems. By flexibly managing interference, RSMA can deliver high spectral and energy efficiency, as well as robustness to imperfect channel state information (CSI). In another development, an intelligent reflecting surface (IRS) has emerged as a method to control the wireless environment through software-configurable, near-passive, sub-wavelength reflecting elements. This article presents the potential of synergy between IRS and RSMA. Three important improvements achievable by IRS-RSMA schemes are identified, supported by insightful numerical examples, and mapped to beyond-5G use cases, along with future research directions.
... The evolution of social networking and the ubiquitous wireless connectivity, coupled with the availability of low-cost yet powerful computing devices jointly shape the next generation of wireless systems. Integrated ground-air-space (IGAS) networks [1] together with new enabling technologies such as large-scale antenna arrays [2], reconfigurable intelligent surfaces [3] and Terahertz communications [4] constitute compelling solutions for the emerging services and applications. Powerful detection schemes play a pivotal role in supporting these novel techniques for achieving their potential gains. ...
... (C. 3) gate σ k z commute and do not contribute to g k , so that the expectation value g k can be computed as follows. ...
Article
Recent advances in quantum technologies pave the way for noisy intermediate-scale quantum (NISQ) devices, where quantum approximation optimization algorithms (QAOAs) constitute promising candidates for demonstrating tangible quantum advantages based on NISQ devices. In this paper, we consider the maximum likelihood (ML) detection problem of binary symbols transmitted over a multiple-input and multiple-output (MIMO) channel, where finding the optimal solution is exponentially hard using classical computers. Here, we apply the QAOA for the ML detection by encoding the problem of interest into a level-p QAOA circuit having 2p variational parameters, which can be optimized by classical optimizers. This level-p QAOA circuit is constructed by applying the prepared Hamiltonian to our problem and the initial Hamiltonian alternately in p consecutive rounds. More explicitly, we first encode the optimal solution of the ML detection problem into the ground state of a problem Hamiltonian. Using the quantum adiabatic evolution technique, we provide both analytical and numerical results for characterizing the evolution of the eigenvalues of the quantum system used for ML detection. Then, for level-1 QAOA circuits, we derive the analytical expressions of the expectation values of the QAOA and discuss the complexity of the QAOA based ML detector. Explicitly, we evaluate the computational complexity of the classical optimizer used and the storage requirement of simulating the QAOA. Finally, we evaluate the bit error rate (BER) of the QAOA based ML detector and compare it both to the classical ML detector and to the classical MMSE detector, demonstrating that the QAOA based ML detector is capable of approaching the performance of the classical ML detector. This paves the way for a host of large-scale classical optimization problems to be solved by NISQ computers.
... Since it is intended to direct all the power received at an IRS towards the UE (in downlink direction) or the TRP (in uplink direction), respectively, UE and TRP are supposed to be in the far-field of the IRS. The far-field condition is fulfilled if the minimum distance d min between IRS-UE (or between IRS-TRP, respectively), is larger than the so-called Fraunhofer distance, which is given as d F = 2l 2 /λ, where λ is the wavelength of the carrier frequency [6]. From this relation, we can derive the maximum size of the IRS (specified by its side length l) for a given minimum distance d min according to ...
... where d is the distance between transmitting and reception point in meters and f is the carrier frequency in GHz. Using the LOS path-loss model (6) in (4) where d 1 and d 2 are the distance between TRP-IRS and IRS-UE, respectively. In the second row, we inserted (2) and used the relation λ = c/f c = 0.3/f , where c = 3 · 10 8 m/s is the speed of light; further we did some conversions in the logdomain, finally yielding the expression in the last row. ...
Conference Paper
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This paper investigates a deployment of intelligent reflecting surfaces (IRS) in a scenario of industrial IoT communication , characterized by data transmission with high reliability under low latency constraints. In this scenario, channel diversity from independent radio links is of supreme importance, which can be enriched by IRS assisted links. By first dimensioning the size of the IRS to fulfill the far-field conditions for the carrier frequency used, the path-loss of the IRS assisted links is modeled based on the 3GPP path-loss models for indoor factories. An analysis of the achievable effective capacity is carried out for selected carrier frequencies in the cm-and mm-wave bands, where it is shown that the IRS deployment can yield significant capacity gains compared to the baseline without IRS.
... However, the main drawback of active relaying is need for a dedicated power supply for amplification, while the drawback of passive reflectors is their limited impact on the coverage due to the inability to dynamically control the reflection angle [2]. A promising solution that combines the benefits of both technologies without their disadvantages has been brought forward by the reconfigurable intelligent surfaces (RISs) paradigm [3][4][5]. ...
... With respect to RIS deployment in communication networks, there has been an intensive investigation in various domains [3]. In addition, when compared to active relaying, which also allows beamforming in an arbitrary direction, several works showcase that sufficiently large RISs can in fact outperform their relay counterparts [4,[6][7][8]. ...
Conference Paper
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In this paper, we examine the potential for a reconfigurable intelligent surface (RIS) to be powered by energy harvested from information signals. This feature might be key to reap the benefits of RIS technology's lower power consumption compared to active relays. We first identify the main RIS power-consuming components and then propose an energy harvesting and power consumption model. Furthermore, we formulate and solve the problem of the optimal RIS placement together with the amplitude and phase response adjustment of its elements in order to maximize the signal-to-noise ratio (SNR) while harvesting sufficient energy for its operation. Finally, numerical results validate the autonomous operation potential and reveal the range of power consumption values that enables it. Index Terms-Reconfigurable intelligent surface, wireless energy harvesting, optimal placement.
... We plot the WSR versus the number of antennas N t , the maximal transmit power P max , and the number of RIS elements M in Fig. 8, Fig. 9, and Fig. 10, respectively. The minimal y ∈ [1,7], and the initial STAR-RIS location is [14,3,2]. Observe that the STAR-RIS is located near the cluster having higher weights, which is in contrast to the beamformer-based NOMA. ...
... shows the optimized location of the STAR-RIS of both the OMA and of the beamformerbased NOMA schemes. The deployment region of the STAR-RIS is set to x ∈[10,14], y ∈[1,7], and the initial location of the STAR-RIS is set to[12,2,2]. For the NOMA scheme, we assume a fixed decoding order, where the transmission based user is detected before the reflection based user. ...
Preprint
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) communication systems are investigated in its vicinity, where a STAR-RIS is deployed within a predefined region for establishing communication links for users. Both beamformer-based NOMA and cluster-based NOMA schemes are employed at the multi-antenna base station (BS). For each scheme, the STAR-RIS deployment location, the passive transmitting and reflecting beamforming (BF) of the STAR-RIS, and the active BF at the BS are jointly optimized for maximizing the weighted sum-rate (WSR) of users. To solve the resultant non-convex problems, an alternating optimization (AO) algorithm is proposed, where successive convex approximation (SCA) and semi-definite programming (SDP) methods are invoked for iteratively addressing the non-convexity of each sub-problem. Numerical results reveal that 1) the WSR performance can be significantly enhanced by optimizing the specific deployment location of the STAR-RIS; 2) both beamformer-based and cluster-based NOMA prefer asymmetric STAR-RIS deployment.
... Similarly, preceding RF signals and depth-images can be exploited for received power prediction in wireless channels, so that resulting outages due to deep fades or channel blockages can be predicted beforehand and managed proactively. Recently, reconfigurable intelligent surface (RIS) aided wireless communication is gaining widespread attention as a means to engineer the propagation environment [25]. An RIS is made of metamaterials with adjustable phase shift and amplitude response. ...
... Novel technologies like the use of RIS are introducing a paradigm shift by allowing to shape the propagation characteristics favorably, and hence are poised to be an integral part of future 6G systems [25], [39]. An RIS-assisted wireless link allows the components of the received signal at a target receiver to add constructively resulting in boosting the received signal-to-noise ratio (SNR). ...
Preprint
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Future industrial applications will encompass compelling new use cases requiring stringent performance guarantees over multiple key performance indicators (KPI) such as reliability, dependability, latency, time synchronization, security, etc. Achieving such stringent and diverse service requirements necessitates the design of a special-purpose Industrial Internet of Things (IIoT) network comprising a multitude of specialized functionalities and technological enablers. This article proposes an innovative architecture for such a special-purpose 6G IIoT network incorporating seven functional building blocks categorized into: special-purpose functionalities and enabling technologies. The former consists of Wireless Environment Control, Traffic/Channel Prediction, Proactive Resource Management and End-to-End Optimization functions; whereas the latter includes Synchronization and Coordination, Machine Learning and Artificial Intelligence Algorithms, and Auxiliary Functions. The proposed architecture aims at providing a resource-efficient and holistic solution for the complex and dynamically challenging requirements imposed by future 6G industrial use cases. Selected test scenarios are provided and assessed to illustrate cross-functional collaboration and demonstrate the applicability of the proposed architecture in a wireless IIoT network.
... Notably, to support high-speed and seamless data services in future wireless systems, a variety of transmission techniques that exploit the implicit randomness of the wireless environment have received increasing attention, such as spatial modulation [2] and massive multiple input and multiple output (MIMO) systems [3]. However, multiple-antenna technologies usually require a high hardware cost and power consumption, and need complex signal processing algorithms [4]- [6]. Existing techniques, in addition, only adapt themselves to the wireless propagation environment. ...
... As far as the IOS is concerned, we consider the same model as in [28]. More precisely, we assume that the IOS elements are partitioned into M groups and that the elements belonging to the same group are set to the same state 4 . This is a typical approach for realizing reconfigurable surfaces at a reduced complexity. ...
Preprint
The intelligent omni-surface (IOS) is a dynamic metasurface that has recently been proposed to achieve full-dimensional communications by realizing the dual function of anomalous reflection and anomalous refraction. Existing research works provide only simplified models for the reflection and refraction responses of the IOS, which do not explicitly depend on the physical structure of the IOS and the angle of incidence of the electromagnetic (EM) wave. Therefore, the available reflection-refraction models are insufficient to characterize the performance of full-dimensional communications. In this paper, we propose a complete and detailed circuit-based reflection-refraction model for the IOS, which is formulated in terms of the physical structure and equivalent circuits of the IOS elements, as well as we validate it against full-wave EM simulations. Based on the proposed circuit-based model for the IOS, we analyze the asymmetry between the reflection and transmission coefficients. Moreover, the proposed circuit-based model is utilized for optimizing the hybrid beamforming of IOS-assisted networks and hence improving the system performance. To verify the circuit-based model, the theoretical findings, and to evaluate the performance of full-dimensional beamforming, we implement a prototype of IOS and deploy an IOS-assisted wireless communication testbed to experimentally measure the beam patterns and to quantify the achievable rate. The obtained experimental results validate the theoretical findings and the accuracy of the proposed circuit-based reflection-refraction model for IOSs.
... Our study shows that, due to design constraints, such as the need of using quantized reflection coefficients or the inherent interplay between the phase and the amplitude of the reflection coefficients, an RIS may 1 1. Nearly-passive reconfigurable devices that are capable of shaping the electromagnetic waves that impinge upon them [8]. Two typical examples are surfaces that reflect or refract, e.g., smart windows, the electromagnetic waves towards non-specular directions. ...
Preprint
Reconfigurable intelligent surface (RIS) is an emerging technology that is under investigation for different applications in wireless communications. RISs are often analyzed and optimized by considering simplified electromagnetic reradiation models. In this chapter, we aim to study the impact of realistic reradiation models for RISs as a function of the sub-wavelength inter-distance between nearby elements of the RIS, the quantization levels of the reflection coefficients, the interplay between the amplitude and phase of the reflection coefficients, and the presence of electromagnetic interference. We consider both case studies in which the users may be located in the far-field and near-field regions of an RIS. Our study shows that, due to design constraints, such as the need of using quantized reflection coefficients or the inherent interplay between the phase and the amplitude of the reflection coefficients, an RIS may reradiate power towards unwanted directions that depend on the intended and interfering electromagnetic waves. Therefore, it is in general important to optimize an RIS by considering the entire reradiation pattern by design to maximize the reradiated power towards the desired directions of reradiation while keeping the power reradiated towards other unwanted directions at a low level. Our study shows that a 2-bit digitally controllable RIS with an almost constant reflection amplitude as a function of the applied phase shift, and whose scattering elements have a size and an inter-distance between (1/8)th and (1/4)th of the signal wavelength may be a good tradeoff between performance, implementation complexity and cost. However, the presented results are preliminary and pave the way for further research into the performance of RISs based on accurate and realistic electromagnetic reradiation models.
... With the system, the average throughput could be reduced by 78 % at the distance of 1 m and 40 % at the distance of 2 m. Furthermore, a good overview about RIS in general and state of research is given by [6] and [17]. With only a few [15], [16] exceptions among the examples in Table I, the phase change of the reflected wave is based on the use of PIN diodes. ...
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One of the frequently discussed topics in the context of the development of Sixth Generation (6G) wireless systems is the feasibility and research of Reconfigurable Intelligent Surfaces (RISs), surfaces consisting of multiple, mostly passive elements that have the ability to manipulate the reflection characteristics of the wireless propagation. Besides theoretical considerations, only a few implementations have been presented which have proposed a working principle of a RIS. For the research of the behavior in a real-world environment, the development of actual working setups will be crucial. In order to simplify the process of research and development of RIS, fundamental questions on design are presented and evaluated. This paper discusses different approaches to create a RIS based on antennas. Therefore, the development of RIS is examined and classified on the basis of various aspects, like design, size and application. The advantages and drawbacks of several antenna designs are compared regarding performance and requirements. Major concerns like real-world efficiency, feasibilities, and known challenges in the construction of a RIS are discussed based on the number of used elements and other general design choices. Possible experimental use cases like the application of Physical Layer Security (PhySec), signal strength enhancements and multiuser scenarios are highlighted. Additionally, real-world RIS scenarios, feasible for current state-of-the-art RISs solutions, are defined while taking into account the major known challenges and concerns of RISs.
... Since RIS does not employ any RF chains, only the cascaded channel, i.e., transmitter-RIS-user, can be estimated, which is, fortunately, sufficient in most cases. However, the RIS elements can be equipped with low-cost dedicated sensors to help CSI acquisition [7]. ...
Article
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Backscatter Communication (BackCom), which is based on passive reflection and modulation of an incident radio-frequency (RF) wave, has emerged as a cutting-edge technological paradigm for self-sustainable Internet-of-things (IoT). Nevertheless , the contemporary BackCom systems are limited to short-range and low data rate applications only, thus rendering them insufficient on their own to support pervasive connectivity among the massive number of IoT devices. Meanwhile, wireless networks are rapidly evolving towards the smart radio paradigm. In this regard, reconfigurable intelligent surfaces (RISs) have come to the forefront to transform the wireless propagation environment into a fully controllable and customizable space in a cost-effective and energy-efficient manner. Targeting the sixth-generation (6G) horizon, we anticipate the integration of RISs into BackCom systems as a new frontier for enabling 6G IoT networks. In this article, for the first time in the open literature, we provide a tutorial overview of RIS-assisted BackCom (RIS-BackCom) systems. Specifically, we introduce the three different variants of RIS-BackCom and identify the potential improvements that can be achieved by incorporating RISs into BackCom systems. In addition, owing to the unrivaled effectiveness of non-orthogonal multiple access (NOMA), we present a case study on an RIS-assisted NOMA-enhanced BackCom system. Finally, we outline the way forward for translating this disruptive concept into real-world applications.
... Specifically, the RIS consisting of low-cost passive elements can work stably without dedicated energy supply. By intelligently tuning the amplitudes and phase shifts of these elements, the RIS is able to modify the wireless channel and customize a favorable smart radio environment (SRE) [6]. With the aid of RISs, the signals from different links can be coherently combined at the legitimate users (Bobs) to constructively enhance the desired signal, or destructively at the eavesdroppers (Eves) to suppress information leakage [7]. ...
Preprint
This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks. In the presence of eavesdroppers, the downlink communication from the base station to the legitimate users is safeguarded by the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS), where three practical operating protocols, namely energy splitting (ES), mode selection (MS), and time splitting (TS), are studied. The joint optimization of power allocation, active and passive beamforming is investigated to maximize the secrecy energy efficiency (SEE), taking into account the imperfect channel state information (CSI) of all channels. For ES, by approximating the semi-infinite constraints with the S-procedure and general sign-definiteness, the problem is solved by an alternating optimization framework. Besides, the proposed algorithm is extended to the MS protocol by solving a mixed-integer non-convex problem. While for TS, a two-layer iterative method is proposed. Simulation results show that: 1) The proposed STAR-RIS assisted NOMA networks are able to provide up to 33.6\% higher SEE than conventional RIS counterparts; 2) TS and ES protocols are generally preferable for low and high power domain, respectively; 3) The accuracy of CSI estimation and the bit resolution power consumption are crucial to reap the SEE benefits offered by STAR-RIS.
... 101017011. through adjustable phase shifts, with the aim of improving system performance in specific locations in space and time [4], [5]. Therefore, owing to their abilities of customizing time-varying wireless propagation environments, RISs mark undeniably the dawn of the 6G era. ...
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... The JCAS system could embrace passive MIMO devices, referred to as RISs, to offer better communication and sensing services. Recent studies show that RISs have great potential in both the communication and sensing fileds [131] [132]. In the context of ICAS, the introduction of an RIS gives more a compatible solution to integrate the communication and sensing functions. ...
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The sixth-generation (6G) network is envisioned to integrate communication and sensing functions, so as to improve the spectrum efficiency (SE) and support explosive novel applications. Although the similarities of wireless communication and radio sensing lay the foundation for their combinations, their different requirements for electromagnetic signals make the joint system design a hard task. To simultaneously guarantee sensing accuracy and communication capacity, the multiple-input and multiple-output (MIMO) technique plays an important role, due to its unique capability of spatial beamforming and waveform shaping. However, the configuration of MIMO also brings high hardware cost, high power consumption, and high signal processing complexity. How to efficiently apply MIMO in the joint communication and sensing (JCAS) system is still open. In this survey, we discuss JCAS in the context of MIMO configurations. We first outline the roles of MIMO in the progress of communication and radar sensing. Then, we review current advances in both communication and sensing coexistence and integration in detail. Three novel JCAS MIMO models are subsequently discussed by introducing the promising 6G enablers, i.e., the unmanned aerial vehicle (UAV) and the reconfigurable intelligent surface (RIS). With the aim of building a compatible dual-function system, the benefits and challenges of MIMO in JCAS are summarized in each subsection. Promising solutions are also discussed from the system perspective with simple, intelligent and robust principles. In the end, open issues are outlined to envisage a comprehensive JCAS network in the near future.
... The primary role of a Reconfigurable Intelligent Surface (RIS) is to mediate a non-line-of-sight link by redirecting the incident beam from the transmitter to the receiver and possibly modifying its characteristics, in order to optimize the beamforming efficiency and to maximize the signal power at the receiver. Its operation is similar to that of a mirror, however the reflection is not limited to specular; depending on the properties of the RIS elements (periodically distributed scatterers forming the RIS surface), the incident beam can be redirected in a controllable manner [1,2]. In recent years, there has been a considerable effort to incorporate the functionalities offered by RISs in millimeter-wave (mmWave) (30-100 GHz) and terahertz (THz) band (0.1-10 THz) communications [3][4][5]. ...
Preprint
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A Reconfigurable Intelligent Surface (RIS) redirects and possibly modifies the properties of incident waves, with the aim to restore non-line-of-sight communication links. Composed of elementary scatterers, the RIS has been so far treated as a collection of point scatterers with properties similar to antennas in an equivalent massive MIMO communication link. Despite the discrete nature of the RIS, current design approaches often treat the RIS as a continuous radiating surface, which is subsequently discretized. Here we investigate the connection between the two approaches in an attempt to bridge the two seemingly opposite perspectives. We analytically find the factor that renders the two approaches equivalent and we demonstrate our findings with examples of RIS elements modeled as antennas with commonly used radiation patterns and properties consistent with antenna theory. The equivalence between the two theoretical approaches is analyzed with respect to design aspects of the RIS elements, such as gain and directivity, with the aim to provide insight into the observed discrepancies, the understanding of which is crucial for assessing the RIS efficiency.
... To solve the challenge, 6G (sixth generation) systems must migrate to several sophisticated network enhancement techniques e.g. IRS [31], [32], THz communication [33], etc. ...
Preprint
Intelligent reflecting surfaces (IRSs) with the ability to reconfigure inherent electromagnetic reflection and absorption characteristics in real-time provide unparalleled prospects to improve wireless connectivity in adverse circumstances. Unmanned aerial vehicles (UAV)-assisted wireless networks are evolved as a reliable solution to combat non-line of sight (NLoS) scenarios. Thereby, the IRS-empowered UAV-assisted cellular networks will be a significant role-player to improve the coverage and user experiences. The paper aimed to minimize the path loss and maximize the achievable data rate in IRS-UAV-assisted networks. In this context, the work analyzed path loss and achievable rate utilizing millimeter wave (mmWave) carrier considering the conventional UAV model and IRS-empowered UAV communication model. The research obtained that the IRSempowered UAV communications model can significantly minimize path loss and maximize the achievable data rate compared to the conventional UAV-assisted model.
... By creating an additional path to bypass potential blockers, reconfigurable intelligent surfaces (RISs) emerge as a solution for mitigating blockages in terrestrial communications [9]. In the context of SatCom, only a few recent works have considered the use of RIS to enhance reception of the SAT This work has been partially funded by Toyota Motor North America. ...
Preprint
Low Earth Orbit (LEO) satellite communications (SatCom) are considered a promising solution to provide uninterrupted services in cellular networks. Line-of-sight (LoS) links between the LEO satellites and the ground users are, however, easily blocked in urban scenarios. In this paper, we propose to enable LEO SatCom in non-line-of-sight (NLoS) channels, as those corresponding to links to users in urban canyons, with the aid of reconfigurable intelligent surfaces (RISs). First, we derive the near field signal model for the satellite-RIS-user link. Then, we propose two deployments to improve the coverage of a RIS-aided link: down tilting the RIS located on the top of a building, and considering a deployment with RISs located on the top of opposite buildings. Simulation results show the effectiveness of using RISs in LEO SatCom to overcome blockages in urban canyons. Insights about the optimal tilt angle and the coverage extension provided by the deployment of an additional RIS are also provided.
... Average power of the transmitted signal λ and fc Wavelength and carrier frequency, respectively G k,n Gain of the RIS k in nth hop ϵ k Efficiency of the RIS k d k, 1 Distance from the source-to-RIS k d k, 2 Distance from the RIS k -to-destination γ and γout Average SNR and predetermined outage threshold, respectively m k,n Shape parameter for Nakagami distribution of RIS k in nth hop Ω k,n Spread parameter for Nakagami distribution of RIS k in nth hop ...
Preprint
This paper analyzes the performance of multiple reconfigurable intelligent surfaces (RISs)-aided networks. The paper also provides some optimization results on the number of reflecting elements on RISs and the optimal placement of RISs. We first derive accurate closed-form approximations for RIS channels' distributions assuming independent non-identically distributed (i.ni.d.) Nakagami-\emph{m} fading environment. Then, the approximate expressions for outage probability (OP) and average symbol error probability are derived in closed-form. Furthermore, to get more insights into the system performance, we derive the asymptotic OP at the high signal-to-noise ratio regime and provide closed-form expressions for the system diversity order and coding gain. Finally, the accuracy of our theoretical analysis is validated through Monte-Carlo simulations. The obtained results show that the considered RIS scenario can provide a diversity order of $\frac{a}{2}K$, where $a$ is a function of the Nakagami fading parameter $m$ and the number of meta-surface elements $N$, and $K$ is the number of RISs.
... Future wireless networks are expected to play a pivotal role in society as they will offer access to intelligent applications such as autonomous driving, virtual and augmented reality etc. [1]. In order to offer ubiquitous services, though, wireless connectivity should be provided for everyone and everywhere [2]. In this context, reconfigurable intelligent surfaces (RISs) have been presented as a solution to realize the concept of smart radio environments (SREs) in which uninterrupted coverage and extremely high quality of service (QoS) can be ensured [3], [4]. ...
... The channels at higher frequencies are also vulnerable to blockage effects, hence the desired line-of-sight link is usually intermittent. This limitation led researches to the conception of a new paradigm for reconfiguring the wireless propagation environment via software-controlled devices for improving the channel conditions with the aid of reconfigurable intelligent surfaces (RISs) [12]. In Industry 4.0 scenarios, inexpensive passive RISs can be deployed for enhancing the channel conditions to boost the system capacity. ...
Article
The fourth industrial revolution, i.e., Industry 4.0, is evolving all around the globe. In this article, we introduce the landscape of Industry 4.0 and beyond empowered by the seamless collaboration of communication technology (CT), information technology (IT), and operation technology (OT), i.e., CIOT collaboration. Specifically, CIOT collaboration is regarded as a main improvement of Industry 4.0 compared to the previous industrial revolutions. We commence by reviewing the previous three industrial revolutions and we argue that the key feature of Industry 4.0 is the CIOT collaboration. More particularly, CT domain supports ubiquitous connectivity of the industrial elements and further bridges the physical world and the cyber world, which is a pivotal prerequisite. Then, we present the potential impacts of CIOT collaboration on typical industrial use cases with the objective of creating a more intelligent and human-friendly industry. Furthermore, the technical challenges of paving the way for the CIOT collaboration with an emphasis on the CT domain are discussed. Finally, we shed light on a roadmap for Industry 4.0 and beyond. The salient steps to be taken in the future CIOT collaboration are highlighted, which may be expected to expedite the paradigm shift towards the next industrial revolution.
... Sixth-generation (6G) network systems have been embarking on significant efforts since current wireless networks may not own the capability for supporting the coming pressure introduced by new applications and massive users. 1 As an emerging paradigm of 6G networks, the intelligent radio environment (IRE) views the wireless environment as an optimization variable to break the limitations of current networks. 2 By deploying the IRE into specific application scenarios, such as point-to-point communication or multi-user communication, empowered wireless networks with great capacity can be consequently obtained. ...
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In this article, we propose the designs of planar pattern manipulation surfaces (PPMSs) applying patch resonating elements loading with dual‐polarized slots for multi‐user communication systems in future networks. Firstly, the amplitude and phase of the element reflection coefficient are discussed with resorting to the varied length of the slot. Secondly, the dual‐polarized slot‐loaded patch is consequently utilized for obtaining the proposed PPMS. By suitably selecting the reflection coefficient distribution of the entire PPMS, the reflected wave can be manipulated to gain different dual‐beam reflection properties with the response of dual‐polarization. In the final, two prototypes with 10 × 10 elements are fabricated and tested to prove the presented design concept. Measurements agree well with calculated results, indicating that dual‐beam reflections with the controllable beam pointing ability are well achieved so as to provide effective coverage for multiple users simultaneously.
... The emerging technique of reconfigurable intelligent surfaces (RISs) have been proposed as a promising candidate for alleviating the unfavorable properties of mmWave signals. RIS is an ultra-thin metasurface comprising multiple programmable elements, which enables to achieve a high beamforming gain by smartly manipulating the incident signal for proactively customizing the radio propagation environment [4]- [6]. More importantly, RIS can significantly reduce the outage caused by the presence of random blockages through establishing virtual line-of-sight (LoS) links between base stations (BSs) and user equipments (UEs), which can considerably enhance the reliability of mmWave communications, especially in harsh urban propagation environments [7]- [9]. ...
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Outdoor-to-indoor communications in millimeter-wave (mmWave) cellular networks have been one challenging research problem due to the severe attenuation and the high penetration loss caused by the propagation characteristics of mmWave signals. We propose a viable solution to implement the outdoor-to-indoor mmWave communication system with the aid of an active intelligent transmitting surface (active-ITS), where the active-ITS allows the incoming signal from an outdoor base station (BS) to pass through the surface and be received by the indoor user-equipments (UEs) after shifting its phase and magnifying its amplitude. Then, the problem of joint precoding of the BS and active-ITS is investigated to maximize the weighted sum-rate (WSR) of the communication system. An efficient block coordinate descent (BCD) based algorithm is developed to solve it with the suboptimal solutions in nearly closed-forms. In addition, to reduce the size and hardware cost of an active-ITS, we provide a block-amplifying architecture to partially remove the circuit components for power-amplifying, where multiple transmissive-type elements (TEs) in each block share a same power amplifier. Simulations indicate that active-ITS has the potential of achieving a given performance with much fewer TEs compared to the passive-ITS under the same total system power consumption, which makes it suitable for application to the size-limited and aesthetic-needed scenario, and the inevitable performance degradation caused by the block-amplifying architecture is acceptable.
... Reconfigurable intelligent surfaces (RISs) have emerged as a promising approach to improve the wireless communication channel quality and to extend the network coverage [1], [2]. However, the vast majority of works consider surfaces that can only reflect the incident signals, which limits the coverage capabilities offered by RISs [3], [4]. ...
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In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves. We focus our attention on the multiple-input multiple-output (MIMO) broadcast channel, and we introduce an algorithm for jointly optimizing the covariance matrix at the base station, the matrix of reflection and transmission coefficients at the IOS, and the amount of power that is reflected and refracted from the IOS. The distinguishable feature of this work lies in taking into account that the reflection and transmission coefficients of an IOS are tightly coupled. Simulation results are illustrated to show the convergence of the proposed algorithm and the benefits of using surfaces with simultaneous reflection and refraction capabilities.
... where δ mk is given in (8) and 0 < α < 1 denotes the fractional power control parameter. ε mk takes different values according to the MR and GMR combining method, which are 1 and w mk respectively. ...
... Towards this goal, multi-input multi-output (MIMO) antenna array architectures have been employed to exploit spatial degrees of freedom (DoFs). Nevertheless, deteriorated performance in uncontrollable electromagnetic environments is still inevitable, which motivates use of the emerging reconfigurable intelligent surface (RIS) technology [3]. ...
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Integrated sensing and communication (ISAC) is emerging as a key enabler to address the growing spectrum congestion problem and satisfy increasing demands for ubiquitous sensing and communication. By sharing various resources and information, ISAC achieves much higher spectral, energy, hardware, and economic efficiencies. Concurrently, reconfigurable intelligent surface (RIS) technology has been deemed as a promising approach due to its capability of intelligently manipulating the wireless propagation environment in an energy and hardware efficient manner. In this article, we analyze the potential of deploying RIS to improve communication and sensing performance in ISAC systems. We first describe the fundamentals of RIS and its applications in traditional communication and sensing systems, then introduce the principles of ISAC and overview existing explorations on RIS-assisted ISAC, followed by one case study to verify the advantages of deploying RIS in ISAC systems. Finally, open challenges and research directions are discussed to stimulate this line of research and pave the way for practical applications.
... To solve the challenge, 6G (sixth generation) systems must migrate to several sophisticated network enhancement techniques e.g. IRS [1], [2], THz communication [3], etc. ...
Conference Paper
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Intelligent reflecting surfaces (IRSs) with the ability to reconfigure inherent electromagnetic reflection and absorption characteristics in real-time provide unparalleled prospects to improve wireless connectivity in adverse circumstances. Unmanned aerial vehicles (UAV)-assisted wireless networks are evolved as a reliable solution to combat non-line of sight (NLoS) scenarios. Thereby, the IRS-empowered UAV-assisted cellular networks will be a significant role-player to improve the coverage and user experiences. The paper aimed to minimize the path loss and maximize the achievable data rate in IRS-UAV-assisted networks. In this context, the work analyzed path loss and achievable rate utilizing millimeter wave (mmWave) carrier considering the conventional UAV model and IRS-empowered UAV communication model. The research obtained that the IRS-empowered UAV communications model can significantly minimize path loss and maximize the achievable data rate compared to the conventional UAV-assisted model.
Article
In this paper, we investigate the transmission design for an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system, where an IRS adjusts its reflection phase shifts to facilitate information transfer and energy harvesting. Two types of input signals, i.e., Gaussian signals and finite-alphabet signals, are both considered. Our goal is to maximize the mutual information between the access point (AP) and the information receiver (IR) by jointly optimizing the transmit beamforming at the AP and the phase shifts of the IRS under the constraints of transmit power at the AP and required harvested energy at the energy harvesting receiver (ER). We show that the transmission designs for these two types of signals actually can be unified into a common optimization problem. Although the formulated problem is an intractable non-convex problem, the solving frameworks in cases of perfect and imperfect channel state information (CSI) are provided, respectively. For the perfect case, an efficient algorithm, which combines semidefinite relaxation (SDR) and penalty-based manifold optimization (PMO), is proposed. For the imperfect case, we study the worst-case transmission design and develop an algorithm based on SDR. Numerical results show the superiority of our proposed algorithms.
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In this paper, the paradigm of thermal noise communication (TherCom) is put forward for future wired/wireless networks with extremely low power consumption. Taking backscatter communication (BackCom) and reconfigurable intelligent surface (RIS)-based radio frequency chain-free transmitters one step further, a thermal noise-driven transmitter might enable zero-signal-power transmission by simply indexing resistors or other noise sources according to information bits. This preliminary paper aims to shed light on the theoretical foundations, transceiver designs, and error performance derivations as well as optimizations of two emerging TherCom solutions: Kirchhoff-law-Johnson-noise (KLJN) secure bit exchange and wireless thermal noise modulation (TherMod) schemes. Our theoretical and computer simulation findings reveal that noise variance detection, supported by sample variance estimation with carefully optimized decision thresholds, is a reliable way of extracting the embedded information from noise modulated signals, even with limited number of noise samples.
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Increasing concerns on intelligent spectrum sensing call for efficient training and inference technologies. In this paper, we propose a novel federated learning (FL) framework, dubbed federated spectrum learning (FSL), which exploits the benefits of reconfigurable intelligent surfaces (RISs) and overcomes the unfavorable impact of deep fading channels. Distinguishingly, we endow conventional RISs with spectrum learning capabilities by leveraging a fully-trained convolutional neural network (CNN) model at each RIS controller, thereby helping the base station to cooperatively infer the users who request to participate in FL at the beginning of each training iteration. To fully exploit the potential of FL and RISs, we address three technical challenges: RISs phase shifts configuration, user-RIS association, and wireless bandwidth allocation. The resulting joint learning, wireless resource allocation, and user-RIS association design is formulated as an optimization problem whose objective is to maximize the system utility while considering the impact of FL prediction accuracy. In this context, the accuracy of FL prediction interplays with the performance of resource optimization. In particular, if the accuracy of the trained CNN model deteriorates, the performance of resource allocation worsens. The proposed FSL framework is tested by using real radio frequency (RF) traces and numerical results demonstrate its advantages in terms of spectrum prediction accuracy and system utility: a better CNN prediction accuracy and FL system utility can be achieved with a larger number of RISs and reflecting elements.
Preprint
With the development of next-generation wireless networks, the Internet of Things (IoT) is evolving towards the intelligent IoT (iIoT), where intelligent applications usually have stringent delay and jitter requirements. In order to provide low-latency services to heterogeneous users in the emerging iIoT, multi-tier computing was proposed by effectively combining edge computing and fog computing. More specifically, multi-tier computing systems compensate for cloud computing through task offloading and dispersing computing tasks to multi-tier nodes along the continuum from the cloud to things. In this paper, we investigate key techniques and directions for wireless communications and resource allocation approaches to enable task offloading in multi-tier computing systems. A multi-tier computing model, with its main functionality and optimization methods, is presented in details. We hope that this paper will serve as a valuable reference and guide to the theoretical, algorithmic, and systematic opportunities of multi-tier computing towards next-generation wireless networks.
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Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions of UM-MIMO and IRS enlarge the near-field region, while strong THz channel sparsity in far-field is detrimental to spatial multiplexing. Moreover, channel estimation (CE) requires recovering the large-scale channel from severely compressed observations due to limited RF-chains. To tackle these challenges, a hybrid spherical- and planar-wave channel model (HSPM) is developed for the cascaded channel of the integrated system. The spatial multiplexing gains under near-field and far-field regions are analyzed, which are found to be limited by the segmented channel with a lower rank. Furthermore, a compressive sensing-based CE framework is developed, including a sparse channel representation method, a separate-side estimation (SSE) and a dictionary-shrinkage estimation (DSE) algorithms. Numerical results verify the effectiveness of the HSPM, the capacity of which is only $5\times10^{-4}$ bits/s/Hz deviated from that obtained by the ground-truth spherical-wave-model, with 256 elements. While the SSE achieves improved accuracy for CE than benchmark algorithms, the DSE is more attractive in noisy environments, with 0.8 dB lower normalized-mean-square-error than SSE.
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In this paper, we propose a mixed radio frequency (RF)/free space optical (FSO) unmanned aerial vehicle (UAV) communication system, based on modulating retro-reflector (MRR) and reconfigurable intelligent surface (RIS), which adopts the hybrid L-ary pulse position modulation-binary phase shift keying-subcarrier intensity modulation (L-PPM-BPSK-SIM). More specifically, the RF channel follows Rayleigh distribution, while the FSO channel obeys Gamma–Gamma distribution that considers atmospheric turbulence and pointing error. For decode-and-forward (DF) relay, the MRR is installed on the UAV to reduce its weight, size, and power consumption. In particular, the RIS is used as user terminal along with the RF signal generator to achieve signal enhancement. Based on this, closed expressions for the outage probability, average bit error rate (BER) and average channel capacity of the end-to-end uplink and downlink are derived. Numerical results confirm that while the relay limitation is solved by MRR, RIS significantly reduces the outage probability and average BER as well as obviously increases the average channel capacity. Furthermore, the hybrid L-PPM-BPSK-SIM with average symbol length greater than eight can effectively improve the average BER performance of the system.
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We exploit multi-path fading propagation to improve both the signal-to-interference-plus-noise-ratio and the stability of wireless communications within electromagnetic environments that support rich multipath propagation. Quasi-passive propagation control with multiple binary reconfigurable intelligent surfaces is adopted to control the stationary waves supported by a metallic cavity hosting a software-defined radio link. Results are demonstrated in terms of the error vector magnitude minimization of a quadrature phase-shift modulation scheme under no-line-of-sight conditions. It is found that the magnitude of fluctuation of received symbols is reduced to a stable constellation by increasing the number of individual surfaces, or elements, thus demonstrating channel hardening. By using a second software-defined radio device as a jammer, we demonstrate the ability of the RIS to mitigate the co-channel interference by channel hardening. Results are of particular interest in smart radio environments for mobile network architectures beyond 5G.
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Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and energy-efficient technique for 6G. By adjusting the phase shifts of passive reflecting elements, RIS is capable of suppressing the interference and combining the desired signals constructively at receivers, thereby significantly enhancing the performance of communication In this paper, we consider a green multi-user multi-antenna cellular network, where multiple RISs are deployed to provide energy-efficient communication service to end users. We jointly optimize the phase shifts of RISs, beamforming of the base stations, and the active RIS set with the aim of minimizing the power consumption of the base station (BS) and RISs subject to the quality of service (QoS) constraints of users and the transmit power constraint of the BS. However, the problem is mixed combinatorial and nonconvex, and there is a potential infeasibility issue when the QoS constraints cannot be guaranteed by all users. To deal with the infeasibility issue, we further investigate a user admission control problem to jointly optimize the transmit beamforming, RIS phase shifts, and the admitted user set. A unified alternating optimization (AO) framework is then proposed to solve both the power minimization and user admission control problems. Specifically, we first decompose the original nonconvex problem into several rank-one constrained optimization subproblems via matrix lifting. The proposed AO framework efficiently minimizes the power consumption of wireless networks as well as user admission control when the QoS constraints cannot be guaranteed by all users. Compared with the baseline algorithms, we illustrate that the proposed algorithm can achieve lower power consumption for given QoS constraints. Most importantly, the proposed algorithm successfully addresses the infeasibility issue with a QoS guarantee for active users.
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Passive intelligent reconfigurable surfaces (IRS) are becoming an attractive component of cellular networks due to their ability of shaping the propagation environment and thereby improving the coverage. While passive IRS nodes incorporate a great number of phase-shifting elements and a controller entity, the phase-shifts are typically determined by the cellular base station (BS) due to its computational capability. Since the fine granularity control of the large number of phase-shifters may become prohibitive in practice, it is important to reduce the control overhead between the BS and the IRS controller. To this end, in this paper we propose a low-rank approximation of the near-optimal phase-shifts, which would incur prohibitively high communication overhead on the BS-IRS controller links. The key idea is to represent the potentially large IRS phase-shift vector using a low-rank tensor model. This is achieved by factorizing a tensorized version of the IRS phase-shift vector, where each component is modeled as the Kronecker product of a predefined number of factors of smaller sizes, which can be obtained via tensor decomposition algorithms. We show that the proposed low-rank models drastically reduce the required feedback requirements associated with the BS-IRS control links. Our simulation results indicate that the proposed method is especially attractive in scenarios with a strong line of sight component, in which case nearly the same spectral efficiency is reached as in the cases with near-optimal phase-shifts, but with a drastically reduced communication overhead.
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Reconfigurable intelligent surfaces (RISs) are two dimensional (2D) 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 paper, we aim at addressing channel characterization and modeling issues of RIS-assisted wireless communication systems. At 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, Doppler effect and multipath fading mitigation, channel reciprocity, channel hardening, rank improvement, far field and near field, etc. RIS based channel modeling works are investigated, including largescale path loss models and small-scale multipath fading models. At last, future research directions related to RIS-assisted channels are also discussed.
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Intelligent reflecting surface (IRS) is a promising technology to enhance the coverage and performance of wireless networks. We consider the application of IRS to non-orthogonal multiple access (NOMA), where a base station transmits superposed signals to multiple users by the virtue of an IRS. The performance of an IRS-assisted NOMA networks with imperfect successive interference cancellation (ipSIC) and perfect successive interference cancellation (pSIC) is investigated by invoking 1-bit coding scheme. In particular, we derive new exact and asymptotic expressions for both outage probability and ergodic rate of the m-th user with ipSIC/pSIC. Based on analytical results, the diversity order of the m-th user with pSIC is in connection with the number of reflecting elements and channel ordering. The high signal-to-noise radio (SNR) slope of ergodic rate for the m-th user is obtained. The throughput and energy efficiency of IRS-NOMA networks are discussed both in delay-limited and delay-tolerant transmission modes. Additionally, we derive new exact expressions of outage probability and ergodic rate for IRS-assisted orthogonal multiple access (IRS-OMA). Numerical results are presented to substantiate our analyses and demonstrate that: i) The outage behaviors of IRS-NOMA are superior to that of IRS-OMA and relaying schemes; ii) The M-th user has a larger ergodic rate than IRS-OMA and benchmarks. However, the ergodic performance of the m-th user exceeds relaying schemes in the low SNR regime; and iii) The IRS-assisted NOMA networks have ability to achieve the enhanced energy efficiency compared to conventional cooperative communications.
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Thanks to the strong ability against the inter-cell interference, cell-free network is considered as a promising technique to improve network capacity. However, further capacity enhancement requires to deploy more base stations (BSs) with high cost and power consumption. To address this issue, inspired by the recently developed reconfigurable intelligent surface (RIS) technique, we propose the concept of RIS-aided cell-free network to improve the capacity with low cost and power consumption. The key idea is to replace some of the required BSs by low-cost and energy-efficient RISs. Then, in a wideband RIS-aided cell-free network, we formulate the problem of joint precoding design at BSs and RISs to maximize the network capacity. Due to the non-convexity and high complexity of the formulated problem, we develop an alternating optimization algorithm to solve this challenging problem. In particular, we decouple this problem via fractional programming, and solve the subproblems alternatively. Note that most of the considered scenarios in existing works are special cases of the general scenario in this paper, and the proposed joint precoding framework can also serve as a general solution to maximize the capacity in most of the existing RIS-aided scenarios. Finally, simulation results demonstrate that, compared with the conventional cell-free network, the network capacity under the proposed scheme can be improved significantly.
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This paper deals with channel estimation in reconfigurable intelligent surface (RIS) aided multiple-input multiple-output (MIMO) time-division duplexing systems. In a typical RIS assisted communication, an RIS is deployed in the close proximity of communication devices, thus resulting in ill-conditioned low-rank channel matrices. To effectively estimate these channels, we propose a two-stage channel estimation method. Specifically, in the first stage, the direct MIMO channel between the end terminals is estimated by utilizing the conventional uplink training approach. In the second stage, after the training process, it is noticed that the RIS channel estimation problem becomes equivalent to a well-known dictionary learning problem. Therefore, we propose to use a bilinear adaptive vector approximate message passing (BAdVAMP) algorithm to estimate RIS channels, which has been shown to be accurate and robust for ill-conditioned dictionary learning problems in compressed sensing. We also propose a phase shift design (passive beamforming) for the RIS by formulating an optimization problem that maximizes the total channel gain at the receiver. Due to its non-convex nature, an approximate closed-form solution is proposed to obtain the phase shift matrix. Numerical results show that the proposed BAdVAMP based RIS channel estimation performs better than its counterpart bilinear generalized AMP (BiGAMP) scheme.
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Employing large intelligent surfaces (LISs) is a promising solution for improving the coverage and rate of future wireless systems. These surfaces comprise massive numbers of nearly-passive elements that interact with the incident signals, for example by reflecting them, in a smart way that improves the wireless system performance. Prior work focused on the design of the LIS reflection matrices assuming full channel knowledge. Estimating these channels at the LIS, however, is a key challenging problem. With the massive number of LIS elements, channel estimation or reflection beam training will be associated with (i) huge training overhead if all the LIS elements are passive (not connected to a baseband) or with (ii) prohibitive hardware complexity and power consumption if all the elements are connected to the baseband through a fully-digital or hybrid analog/digital architecture. This paper proposes efficient solutions for these problems by leveraging tools from compressive sensing and deep learning. First, a novel LIS architecture based on sparse channel sensors is proposed. In this architecture, all the LIS elements are passive except for a few elements that are active (connected to the baseband). We then develop two solutions that design the LIS reflection matrices with negligible training overhead. In the first approach, we leverage compressive sensing tools to construct the channels at all the LIS elements from the channels seen only at the active elements. In the second approach, we develop a deep-learning based solution where the LIS learns how to interact with the incident signal given the channels at the active elements, which represent the state of the environment and transmitter/receiver locations. We show that the achievable rates of the proposed solutions approach the upper bound, which assumes perfect channel knowledge, with negligible training overhead and with only a few active elements, making them promising for future LIS systems.
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Reconfigurable intelligent surfaces (RISs) have recently emerged as a promising technology that can achieve high spectrum and energy efficiency for future wireless networks by integrating a massive number of low-cost and passive reflecting elements. An RIS can manipulate the properties of an incident wave, such as the frequency, amplitude, and phase, and, then, reflect this manipulated wave to a desired destination, without the need for complex signal processing. In this paper, the asymptotic optimality of achievable rate in a downlink RIS system is analyzed under a practical RIS environment with its associated limitations. In particular, a passive beamformer that can achieve the asymptotic optimal performance by controlling the incident wave properties is designed, under a limited RIS control link and practical reflection coefficients. In order to increase the achievable system sum-rate, a modulation scheme that can be used in an RIS without interfering with existing users is proposed and its average symbol error rate is asymptotically derived. Moreover, a new resource allocation algorithm that jointly considers user scheduling and power control is designed, under consideration of the proposed passive beamforming and modulation schemes. Simulation results show that the proposed schemes are in close agreement with their upper bounds in presence of a large number of RIS reflecting elements thereby verifying that the achievable rate in practical RISs satisfies the asymptotic optimality.
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Terahertz (THz) communications open a new frontier for the wireless network thanks to their dramatically wider available bandwidth compared to the current micro-wave and forthcoming millimeter-wave communications. However, due to the short length of THz waves, they also suffer from severe path attenuation and poor diffraction. To compensate the THz-induced propagation loss, this paper proposes to combine two promising techniques, viz., massive multiple input multiple output (MIMO) and intelligent reflecting surface (IRS), in THz multi-user communications, considering their significant beamforming and aperture gains. Nonetheless, channel estimation and low-cost beamforming turn out to be two main obstacles to realizing this combination, due to the passivity of IRS for sending/receiving pilot signals and the large-scale use of expensive RF chains in massive MIMO. In view of these limitations, this paper first develops a cooperative beam training scheme to facilitate the channel estimation with IRS. In particular, we design two different hierarchical codebooks for the proposed training procedure, which are able to balance between the robustness against noise and searching complexity. Based on the training results, we further propose two cost-efficient hybrid beamforming (HB) designs for both single-user and multi-user scenarios, respectively. Simulation results demonstrate that the proposed joint beam training and HB scheme is able to achieve close performance to the optimal fully digital beamforming which is implemented even under perfect channel state information (CSI).
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Intelligent reflecting surfaces (IRSs) have emerged as a revolutionary solution to enhance wireless communications by changing propagation environment in a cost-effective and hardware-efficient fashion. In addition, symbol-level precoding (SLP) has attracted considerable attention recently due to its advantages in converting multiuser interference (MUI) into useful signal energy. Therefore, it is of interest to investigate the employment of IRS in symbol-level precoding systems to exploit MUI in a more effective way by manipulating the multiuser channels. In this paper, we focus on joint symbol-level precoding and reflecting designs in IRS-enhanced multiuser multiple-input single-output (MU-MISO) systems. Both power minimization and quality-of-service (QoS) balancing problems are considered. In order to solve the joint optimization problems, we develop an efficient iterative algorithm to decompose them into separate symbol-level precoding and block-level reflecting design problems. An efficient gradient-projection-based algorithm is utilized to design the symbol-level precoding and a Riemannian conjugate gradient (RCG)-based algorithm is employed to solve the reflecting design problem. Simulation results demonstrate the significant performance improvement introduced by the IRS and illustrate the effectiveness of our proposed algorithms.
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Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this paper, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying the physics and electromagnetic nature of RISs. The proposed models, which are first validated through extensive simulation results, reveal the relationships between the free-space path loss of RIS-assisted wireless communications and the distances from the transmitter/receiver to the RIS, the size of the RIS, the near-field/far-field effects of the RIS, and the radiation patterns of antennas and unit cells. In addition, three fabricated RISs (metasurfaces) are utilized to further corroborate the theoretical findings through experimental measurements conducted in a microwave anechoic chamber. The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.
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In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system, where an IRS is deployed to adjust its reflecting elements to secure the communication of multiple legitimate users in the presence of multiple eavesdroppers. Aiming to improve the system secrecy rate, a design problem for jointly optimizing the base station (BS)’s beamforming and the IRS’s reflecting beamforming is formulated considering different quality of service (QoS) requirements and time-varying channel conditions. As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments. Furthermore, post-decision state (PDS) and prioritized experience replay (PER) schemes are utilized to enhance the learning efficiency and secrecy performance. Specifically, a modified PDS scheme is presented to trace the channel dynamic and adjust the beamforming policy against channel uncertainty accordingly. Simulation results demonstrate that the proposed deep PDS-PER learning based secure beamforming approach can significantly improve the system secrecy rate and QoS satisfaction probability in IRS-aided secure communication systems.
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Millimeter wave communication is eminently suitable for high-rate wireless systems, which may be beneficially amalgamated with intelligent reflecting surfaces (IRS), while relying on beam-index modulation. Explicitly, we propose three different architectures based on IRSs for beam-index modulation in millimeter wave communication. Our schemes are capable of eliminating the detrimental line-of-sight blockage of millimeter wave frequencies.The schemes are termed as single-symbol beam index modulation, multi-symbol beam-index modulation and maximum-SNR single-symbol beam index modulation. The principle behind these is to embed the information both in classic QAM/PSK symbols and in the transmitter beam-pattern. Explicitly, we proposed to use a twin-IRS structure to construct a low-cost beamindex modulation scheme. We conceive both the optimal maximum likelihood detector and a low-complexity compressed sensing detector for the proposed schemes. Finally, the schemes designed are evaluated through extensive simulations and the results are compared to our analytical bounds.
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This paper considers an artificial noise (AN)-aided secure MIMO wireless communication system. To enhance the system security performance, the advanced intelligent reflecting surface (IRS) is invoked, and the base station (BS), legitimate information receiver (IR) and eavesdropper (Eve) are equipped with multiple antennas. With the aim for maximizing the secrecy rate (SR), the transmit precoding (TPC) matrix at the BS, covariance matrix of AN and phase shifts at the IRS are jointly optimized subject to constrains of transmit power limit and unit modulus of IRS phase shifts. Then, the secrecy rate maximization (SRM) problem is formulated, which is a non-convex problem with multiple coupled variables. To tackle it, we propose to utilize the block coordinate descent (BCD) algorithm to alternately update the variables while keeping SR non-decreasing. Specifically, the optimal TPC matrix and AN covariance matrix are derived by Lagrangian multiplier method, and the optimal phase shifts are obtained by Majorization-Minimization (MM) algorithm. Since all variables can be calculated in closed form, the proposed algorithm is very efficient. We also extend the SRM problem to the more general multiple-IRs scenario and propose a BCD algorithm to solve it. Simulation results validate the effectiveness of system security enhancement via an IRS.
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The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since these can relay signals to achieve an SNR that grows as N2, which seems like a major benefit. In this paper, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where N∞. We derive an exact channel gain expression that captures three essential near-field behaviors and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how much larger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behave as an “anomalous” mirror but can vastly outperform that benchmark.
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In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple user pairs in two-hop networks is investigated. Different from the existing studies on IRS that mainly focused on tuning the reflection coefficients of all elements, we consider the implementation of true reflection resource management (RRM) through the identification of the best triggered module subset. More precisely, the implementation of true RRM builds on the premise of our proposed modular IRS structure consisting of multiple independent and controllable modules. In the context of modular IRS structure, we investigate the signal-to-interference-plus-noise ratio (SINR)-based max-min problem subject to per source terminals (STs) power budgets and module size constraint, via joint triggered module subset identification, transmit power allocation, and the corresponding passive beamforming. Whereas this problem is NP-hard due to the module size constraint, which can be addressed by the convex sparsity-inducing approximation to the hard module size constraint using mixed ℓ1,F-norm, where it yields a suitable semidefinite relaxation. Using techniques from separable convex programming, we provide a two-block alternating direction method of multipliers (ADMM) algorithm for the approximated problem. Numerical simulations are used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters. Further energy efficiency (EE) performance comparison demonstrates the necessity and meaningfulness of the introduced modular IRS structure. Specifically, for a given network setting, there is an optimal value of the number of triggered modules for system, when the EE is considered.
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In this paper, we introduce a physics-consistent analytical characterization of the free-space path-loss of a wireless link in the presence of a reconfigurable intelligent surface. The proposed approach is based on the vector generalization of Green’s theorem. The obtained path-loss model can be applied to two-dimensional homogenized metasurfaces, which are made of sub-wavelength scattering elements and that operate either in reflection or transmission mode. The path-loss is formulated in terms of a computable integral that depends on the transmission distances, the polarization of the radio waves, the size of the surface, and the desired surface transformation. Closed-form expressions are obtained in two asymptotic regimes that are representative of far-field and near-field deployments. Based on the proposed approach, the impact of several design parameters and operating regimes is unveiled.
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Power-domain non-orthogonal multiple access (NOMA) has become a promising technology to exploit the new dimension of the power domain to enhance the spectral efficiency of wireless networks. However, most existing NOMA schemes rely on the strong assumption that users’ channel gains are quite different, which may be invalid in practice. To unleash the potential of power-domain NOMA, we propose a reconfigurable intelligent surface (RIS)-empowered NOMA scheme to introduce desirable channel gain differences among the users by adjusting the phase shifts at the RIS. Our goal is to minimize the total transmit power by jointly optimizing the beamforming vectors at the base station, the phase-shift matrix at the RIS, and user ordering. To address challenge due to the highly coupled optimization variables, we present an alternating optimization framework to decompose the non-convex bi-quadratically constrained quadratic problem under a specific user ordering into two rank-one constrained matrices optimization problems via matrix lifting. To accurately detect the feasibility of the non-convex rank-one constraints and improve performance by avoiding early stopping in the alternating optimization procedure, we equivalently represent the rank-one constraint as the difference between nuclear norm and spectral norm. A difference-of-convex (DC) algorithm is further developed to solve the resulting DC programs via successive convex relaxation, followed by establishing the convergence of the proposed DC-based alternating optimization method. We further propose an efficient user ordering scheme with closed-form expressions, considering both the channel conditions and users’ target data rates. Simulation results validate the ability of an RIS in enlarging the channel-gain difference when the users’ original channel conditions are similar and the superiority of the proposed DC-based alternating optimization method in reducing the total transmit power.
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The fundamental capacity limits of intelligent reflecting surface (IRS)-assisted multi-user wireless communication systems are investigated in this paper. Specifically, the capacity and rate regions for both capacity-achieving non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) transmission schemes are characterized by jointly optimizing the IRS reflection matrix and wireless resource allocation under the constraints of a maximum number of IRS reconfiguration times. In NOMA, all users are served in the same resource blocks by employing superposition coding and successive interference cancelation techniques. In OMA, all users are served by being allocated orthogonal resource blocks of different sizes. For NOMA, the ideal case with an asymptotically large number of IRS reconfiguration times is firstly considered, where the optimal solution is obtained by employing the Lagrange duality method. Inspired by this result, an inner bound of the capacity region for the general case with a finite number of IRS reconfiguration times is derived. For OMA, the optimal transmission strategy for the ideal case is to serve each individual user alternatingly with its effective channel power gain maximized. Based on this result, a rate region inner bound for the general case is derived. Finally, numerical results are provided to show that: i) a significant capacity and rate region improvement can be achieved by using IRS; ii) the capacity gain can be further improved by dynamically configuring the IRS reflection matrix.
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Metasurfaces have drawn significant attentions due to their superior capability in tailoring electromagnetic waves with a wide frequency range, from microwave to visible light. Recently, programmable metasurfaces have demonstrated the ability of manipulating the amplitude or phase of electromagnetic waves in a programmable manner in real time, which renders them especially appealing in the applications of wireless communications. In this paper, we present the fundamental principle of applying programmable metasurface as transmitter for wireless communications. Then, we establish a prototype system of meta-surface-based transmitter to conduct several experiments and measurements over the air, which practically demonstrate the feasibility of using programmable metasurfaces in future communication systems. By exploiting the dynamically controllable property of programmable metasurface, the design, implementation and experimental evaluation of the proposed metasurface-based wireless communication system are presented with the prototype, which realizes single carrier quadrature phase shift keying (QPSK) transmission over the air. In the developed prototype, the phase of the reflected electromagnetic wave of programmable metasurface is directly manipulated in real time according to the baseband control signal, which achieves 2.048 Mbps data transfer rate with video streaming transmission over the air. In addition, experimental result is provided to compare the performance of the proposed metasurface-based architecture against the conventional one. With the slight increase of the transmit power by 5 dB, the same bit error rate (BER) performance can be achieved as the conventional system in the absence of channel coding. Such a result is encouraging considering that the metasurface-based system has the advantages of low hardware cost and simple structure, thus leading to a promising new architecture for wireless communications.
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In this paper, an intelligent reflecting surface (IRS)-aided secure wireless information and power transfer system is studied. To maximize the harvested power of energy harvesting receiver (EHR), we optimize the secure transmit beamforming at the access point (AP) and phase shifts at the IRS subject to the secrecy rate (SR) and the reflecting phase shifts at the IRS constraints. Due to the non-convexity of optimization problem and coupled optimization variables, we convert the optimization problem into a semidefinite relaxation (SDR) problem and a sub-optimal solution is obtained. To reduce the high-complexity of the proposed SDR method, a low-complexity alternating optimization (LC-AO) algorithm is proposed. Simulation results show that the harvested power of the proposed SDR and LC-AO methods approximately double that of the existing method without IRS with the same SR. In particular, the proposed LC-AO achieves almost the same performance as the proposed SDR but with a much lower complexity.
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In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the same performance as computationally complex dirty paper coding, where the quasi-degradation condition is satisfied, conditioned on the users’ channels fall in the quasi-degradation region. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we focus on an IRS-assisted MISO NOMA system, where the wireless channels can be effectively tuned. We optimize the beamforming vectors and the IRS phase shift matrix for minimizing transmission power. Furthermore, we propose an improved quasi-degradation condition by using IRS, which can ensure that NOMA achieves the capacity region with high possibility. For a comparison, we study zero-forcing beamforming (ZFBF) as well, where the beamforming vectors and the IRS phase shift matrix are also jointly optimized. Comparing NOMA with ZFBF, it is shown that, with the same IRS phase shift matrix and the improved quasi-degradation condition, NOMA always outperforms ZFBF. At the same time, we identify the condition under which ZFBF outperforms NOMA, which motivates the proposed hybrid NOMA transmission. Simulation results show that the proposed IRS-assisted MISO system outperforms the MISO case without IRS, and the hybrid NOMA transmission scheme always achieves better performance than orthogonal multiple access.
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Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple PU receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.
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In this article, we introduce Wireless 2.0, the future generation of wireless communication networks, in which the radio environment becomes controllable and intelligent by leveraging the emerging technologies of reconfigurable metasurfaces (RMSs) and artificial intelligence (AI). In particular, we emphasize AI-based computational methods and commence with an overview of the concept of intelligent radio environments (IREs) based on RMSs. Then, we elaborate on data management aspects, the requirements of supervised learning by examples, and the paradigm of reinforcement learning to learn by acting. Finally, we highlight numerous open challenges and research directions.
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Reconfigurable intelligent surfaces have emerged as a promising technology for future wireless networks. Given that a large number of reflecting elements is typically used and that the surface has no signal processing capabilities, a major challenge is to cope with the overhead that is required to estimate the channel state information and to report the optimized phase shifts to the surface. This issue has not been addressed by previous works, which do not explicitly consider the overhead during the resource allocation phase. This work aims at filling this gap, by developing an overhead-aware resource allocation framework for wireless networks where reconfigurable intelligent surfaces are used to improve the communication performance. An overhead model is proposed and incorporated in the expressions of the system rate and energy efficiency, which are then optimized with respect to the phase shifts of the reconfigurable intelligent surface, the transmit and receive filters, the power and bandwidth used for the communication and feedback phases. The bi-objective maximization of the rate and energy efficiency is investigated, too. The proposed framework characterizes the trade-off between optimized radio resource allocation policies and the related overhead in networks with reconfigurable intelligent surfaces.
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