Showing papers in "IEEE Wireless Communications Letters in 2021"
TL;DR: In this paper, an alternative physically feasible Rayleigh fading model that can be used as a baseline when evaluating RIS-aided communications is presented. But the model is not physically appearing when using a reconfigurable intelligent surface (RIS) with rectangular geometry.
Abstract: A realistic performance assessment of any wireless technology requires the use of a channel model that reflects its main characteristics. The independent and identically distributed Rayleigh fading channel model has been (and still is) the basis of most theoretical research on multiple antenna technologies in scattering environments. This letter shows that such a model is not physically appearing when using a reconfigurable intelligent surface (RIS) with rectangular geometry and provides an alternative physically feasible Rayleigh fading model that can be used as a baseline when evaluating RIS-aided communications. The model is used to revisit the basic RIS properties, e.g., the rank of spatial correlation matrices and channel hardening.
187 citations
TL;DR: A physics and electromagnetic (EM) compliant communication model for analyzing and optimizing RIS-assisted wireless systems and accounts for the intertwinement between the amplitude and phase response of the unit cells of the RIS.
Abstract: Reconfigurable intelligent surfaces (RISs) are an emerging technology for application to wireless networks. We introduce a physics and electromagnetic (EM) compliant communication model for analyzing and optimizing RIS-assisted wireless systems. The proposed model has four main notable attributes: (i) it is end-to-end , i.e., it is formulated in terms of an equivalent channel that yields a one-to-one mapping between the voltages fed into the ports of a transmitter and the voltages measured at the ports of a receiver; (ii) it is EM-compliant , i.e., it accounts for the generation and propagation of the EM fields; (iii) it is mutual coupling aware , i.e., it accounts for the mutual coupling among the sub-wavelength unit cells of the RIS; and (iv) it is unit cell aware , i.e., it accounts for the intertwinement between the amplitude and phase response of the unit cells of the RIS.
121 citations
TL;DR: The impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system that provides MEC services to multiple Internet of Thing devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed.
Abstract: This letter studies the impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system. Specifically, an access point (AP) equipped with an edge server provides MEC services to multiple Internet of Thing (IoT) devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed. We deploy an IRS to enhance the computational performance of the MEC system by intelligently adjusting the phase shift of each reflecting element. A joint design problem is formulated for the considered IRS assisted MEC system, aiming to optimize its sum computational bits and taking into account the CPU frequency, the offloading time allocation, transmit power of each device as well as the phase shifts of the IRS. To deal with the non-convexity of the formulated problem, we conduct our algorithm design by finding the optimized phase shifts first and then achieving the jointly optimal solution of the CPU frequency, the transmit power and the offloading time allocation by considering the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Numerical evaluations highlight the advantage of the IRS-assisted MEC system in comparison with the benchmark schemes.
117 citations
TL;DR: This letter proposes a novel secure intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) system, where the UAV sends confidential messages to a legitimate receiver, in the presence of a passive eavesdropper, using an iterative algorithm based on successive convex approximation (SCA).
Abstract: This letter proposes a novel secure intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) system, where the UAV sends confidential messages to a legitimate receiver, in the presence of a passive eavesdropper. We aim to maximize the secrecy rate by jointly designing the trajectory, the power control of UAV and the phase shifters of the IRS from the physical layer security perspective. Because the formulated problem is non-convex and intractable, we propose an iterative algorithm based on successive convex approximation (SCA) to solve this problem. Simulation results validate the effectiveness of the proposed algorithm and show that the secrecy rate is significantly improved with the assistance of the IRS.
114 citations
TL;DR: This letter presents a secure beamforming (BF) scheme for RSMA-based cognitive satellite terrestrial networks in the presence of multiple eavesdroppers and proposes a robust BF scheme to convert the nonconvex objective and constraints into convex ones, which can be iteratively solved.
Abstract: Rate-splitting multiple access (RSMA) has recently received considerable attention due to its high efficiency in both spectral utilization and energy consumption. Inspired by this emerging technique, this letter presents a secure beamforming (BF) scheme for RSMA-based cognitive satellite terrestrial networks in the presence of multiple eavesdroppers. Assuming that the system operates in the millimeter wave band and only imperfect wiretap channel state information is available at the satellite and terrestrial base station, our objective is to maximize the secrecy-energy efficiency of the earth station (ES) while meeting the constraints on the ES secrecy rate, the cellular users’ rate requirements, and transmit power budgets of the satellite and base station. As the formulated optimization problem is mathematically intractable, by applying successive convex approximation and Taylor expansion methods, we propose a robust BF scheme to convert the nonconvex objective and constraints into convex ones, which can be iteratively solved. The effectiveness and superiority of the proposed scheme are confirmed through simulation results.
107 citations
TL;DR: An iteration algorithm based on successive Convex Approximation with the Rate constraint penalty (CAR) is developed to obtain UAV’s trajectory, and the IRS phase shift is formulated as a closed-form expression with introduced pricing factors.
Abstract: In this letter, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications. To this end, the joint optimization of UAV’s trajectory, the phase shift of IRS, the allocation of THz sub-bands, and the power control are investigated to maximize the minimum average achievable rate of all users. An iteration algorithm based on successive Convex Approximation with the Rate constraint penalty (CAR) is developed to obtain UAV’s trajectory, and the IRS phase shift is formulated as a closed-form expression with introduced pricing factors. Simulation results show that the proposed scheme significantly enhances the rate performance of the whole system.
107 citations
TL;DR: In this paper, the authors consider a fading channel in which a multi-antenna transmitter communicates with a multiantenna receiver through a reconfigurable intelligent surface (RIS) that is made of ${N}$ passive scatterers impaired by phase noise.
Abstract: We consider a fading channel in which a multi-antenna transmitter communicates with a multi-antenna receiver through a reconfigurable intelligent surface (RIS) that is made of ${N}$ reconfigurable passive scatterers impaired by phase noise. The beamforming vector at the transmitter, the combining vector at the receiver, and the phase shifts of the ${N}$ scatterers are optimized in order to maximize the signal-to-noise-ratio (SNR) at the receiver. By assuming Rayleigh fading (or line-of-sight propagation) on the transmitter-RIS link and Rayleigh fading on the RIS-receiver link, we prove that the SNR is a random variable that is equivalent in distribution to the product of three (or two) independent random variables whose distributions are approximated by two (or one) gamma random variables and the sum of two scaled non-central chi-square random variables. The proposed analytical framework allows us to quantify the robustness of RIS-aided transmission to fading channels. For example, we prove that the amount of fading experienced on the transmitter-RIS-receiver channel linearly decreases with ${N}~\gg ~1.$ This proves that RISs of large size can be effectively employed to make fading less severe and wireless channels more reliable.
101 citations
TL;DR: It is proved that dynamic IRS beamforming is not needed for the considered system, which helps reduce the number of IRS phase shifts to be optimized and both joint and alternating optimization based algorithms are proposed to solve the resulting problem.
Abstract: Intelligent reflecting surface (IRS) is a promising technology to improve the performance of wireless powered communication networks (WPCNs) due to its capability to reconfigure signal propagation environments via smart reflection. In particular, the high passive beamforming gain promised by IRS can significantly enhance the efficiency of both downlink wireless power transfer (DL WPT) and uplink wireless information transmission (UL WIT) in WPCNs. Although adopting different IRS phase shifts for DL WPT and UL WIT, i.e., dynamic IRS beamforming , is in principle possible but incurs additional signaling overhead and computational complexity, it is an open problem whether it is actually beneficial. To answer this question, we consider an IRS-assisted WPCN where multiple devices employ a hybrid access point (HAP) to first harvest energy and then transmit information using non-orthogonal multiple access (NOMA). Specifically, we aim to maximize the sum throughput of all devices by jointly optimizing the IRS phase shifts and the resource allocation. To this end, we first prove that dynamic IRS beamforming is not needed for the considered system, which helps reduce the number of IRS phase shifts to be optimized. Then, we propose both joint and alternating optimization based algorithms to solve the resulting problem. Simulation results demonstrate the effectiveness of our proposed designs over benchmark schemes and also provide useful insights into the importance of IRS for realizing spectrum and energy efficient WPCNs.
82 citations
TL;DR: A novel and effective twin-DDPG deep reinforcement learning (TDDRL) algorithm is proposed that can significantly improve the sum secrecy rate in the millimeter-wave (mmWave) unmanned aerial vehicle communication assisted by a reconfigurable intelligent surface (RIS).
Abstract: In this letter, we study the robust and secure transmission in the millimeter-wave (mmWave) unmanned aerial vehicle (UAV) communication assisted by a reconfigurable intelligent surface (RIS) under imperfect channel state information (CSI). Specifically, the active beamforming of the UAV, the coefficients of the RIS elements and the UAV trajectory are jointly designed to maximize the sum secrecy rate of all legitimate users in the presence of multiple eavesdroppers. However, the CSI is coupled with the UAV trajectory, which results in complex constraints. Furthermore, the time-related issue caused by the outdated CSI also makes the formulated problem intractable to solve. To tackle these challenges, by leveraging the deep deterministic policy gradient (DDPG) framework, a novel and effective twin-DDPG deep reinforcement learning (TDDRL) algorithm is proposed. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm, and the RIS can significantly improve the sum secrecy rate.
78 citations
TL;DR: A novel closed-form expression of the outage probability for arbitrary phase shifts and correlation matrices of the indirect channels is derived and two common scenarios met in the literature when the large-scale fading coefficients are expressed by the loss over a propagation distance are met.
Abstract: This letter investigates the impact of spatial channel correlation on the outage probability of intelligent reflecting surface (IRS)-assisted single-input single-output (SISO) communication systems. In particular, we derive a novel closed-form expression of the outage probability for arbitrary phase shifts and correlation matrices of the indirect channels. To shed light on the impact of the spatial correlation, we further attain the closed-form expressions for two common scenarios met in the literature when the large-scale fading coefficients are expressed by the loss over a propagation distance. Numerical results validate the tightness and effectiveness of the closed-form expressions. Furthermore, the spatial correlation offers significant decreases in the outage probability as the direct channel is blocked.
77 citations
TL;DR: A modulation for unsourced massive random access whereby the transmitted symbols are rank-1 tensors constructed from Grassmannian sub-constellations, together with tensor decomposition, allows a convenient uncoupling between multi-user separation and single-user demapping.
Abstract: We introduce a modulation for unsourced massive random access whereby the transmitted symbols are rank-1 tensors constructed from Grassmannian sub-constellations. The use of a low-rank tensor structure, together with tensor decomposition in order to separate the users at the receiver, allows a convenient uncoupling between multi-user separation and single-user demapping. The proposed signaling scheme is designed for the block fading channel and multiple-antenna settings, and is shown to perform well in comparison to state-of-the-art approaches.
TL;DR: In this paper, the authors studied efficient channel estimation and passive beamforming designs for a double-intelligent reflecting surface (IRS) aided single-user communication system, where a user communicates with an access point (AP) via the cascaded user-IRS 1IRS 2-AP double-reflection link.
Abstract: In this letter, we study efficient channel estimation and passive beamforming designs for a double-intelligent reflecting surface (IRS) aided single-user communication system, where a user communicates with an access point (AP) via the cascaded user-IRS 1-IRS 2-AP double-reflection link. First, a general channel estimation scheme is proposed for the system under any arbitrary inter-IRS channel, where all coefficients of the cascaded channel are estimated. Next, for the typical scenario with a line-of-sight (LoS)-dominant inter-IRS channel, we propose another customized scheme to estimate two signature vectors of the rank-one cascaded channel with significantly less channel training time than the first scheme. For the two proposed channel estimation schemes, we further optimize their corresponding cooperative passive beamforming for data transmission to maximize the achievable rate with the training overhead and channel estimation error taken into account. Numerical results show that deploying two cooperative IRSs with the proposed channel estimation and passive beamforming designs achieves significant rate enhancement as compared to the conventional case of single IRS deployment.
TL;DR: A data-aided channel estimation algorithm for a superimposed pilot and data transmission scheme, which can improve the spectral efficiency and coarsely estimate the channel based on the pilot symbol, followed by an iterative process which detects the data symbols and refines the channel estimates.
Abstract: The recently developed orthogonal time frequency space (OTFS) modulation has shown its capability of coping with the fast time-varying channels in high-mobility environments. In particular, OTFS modulation gives rise to the sparse representation of the delay-Doppler (DD) domain channel model. Hence, one can an enjoy accurate channel estimation by adopting only one pilot symbol. However, conventional OTFS channel estimation schemes require the deployment of guard space to avoid data-pilot interference, which inevitably sacrifices the spectral efficiency. In this letter, we develop a data-aided channel estimation algorithm for a superimposed pilot and data transmission scheme, which can improve the spectral efficiency. To accurately estimate the channel and detect the data symbols, we coarsely estimate the channel based on the pilot symbol, followed by an iterative process which detects the data symbols and refines the channel estimates. Simulation results show that the bit error rate (BER) performance based on the proposed method can approach the baseline scheme with perfect channel estimation.
TL;DR: Comparisons with relay-aided systems are carried out to demonstrate that the proposed system setup outperforms relaying schemes both in terms of the OP and average sum-rate and shows that the number of RISs as well as theNumber of reflecting elements play a crucial role in the capacity scaling law of multiple RIS-aiding networks.
Abstract: In this letter, we consider a network assisted by multiple reconfigurable intelligent surfaces (RISs). Assuming that the RIS with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is selected to aid the communication, the outage probability (OP) and average sum-rate are investigated. Specifically, an exact analysis for the OP is developed. In addition, relying on the extreme value theory, a closed-form expression for the asymptotic sum-rate is derived, based on which the capacity scaling law is established. Our results are corroborated through simulations and insightful discussions are provided. In particular, our analysis shows that the number of RISs as well as the number of reflecting elements play a crucial role in the capacity scaling law of multiple RIS-aided networks. Also, comparisons with relay-aided systems are carried out to demonstrate that the proposed system setup outperforms relaying schemes both in terms of the OP and average sum-rate.
TL;DR: This letter studies a multiuser multiple-input single-output (MISO) intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system and proposes an efficient algorithm for solving two subproblems based on the alternating optimization (AO).
Abstract: This letter studies a multiuser multiple-input single-output (MISO) intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits data along with energy to a set of users to decode data and harvest energy by adopting the power splitting (PS) simultaneously. The energy efficiency indicator (EEI) is introduced to trade off between data rate and harvested energy, which is maximized by jointly optimizing beamforming vectors at the BS, PS ratio at each user, and phase shifts at the IRS. To solve this non-convex optimization problem, we first adopt the majorization-minimization (MM) approach to construct a concave-convex fractional function which can be handled via the Dinkelbach algorithm and then propose an efficient algorithm for solving two subproblems based on the alternating optimization (AO). For the first subproblem, semi-definite relaxation (SDR), MM approach, and Dinkelbach algorithm are adopted, while for the second sub-problem, a new manifold approach is proposed to handle the unit-modulus constraints due to IRS passive reflection. Simulation results demonstrate the superior performance of our proposed algorithm compared to other baseline schemes.
TL;DR: In this article, the authors proposed an energy-efficient resource allocation (RA) problem in NOMA-backscatter communication networks with QoS guarantee, where the transmit power of the base station and the reflection coefficient of the backscatter device are jointly optimized.
Abstract: Energy efficiency (EE) is an important performance metric in communication systems. However, to the best of our knowledge, the energy-efficient resource allocation (RA) problem in non-orthogonal multiple access enabled backscatter communication networks (NOMA-BackComNet) comprehensively considering the user’s quality of service (QoS) has not been investigated. In this letter, we present the first attempt to solve the EE-based RA problem for NOMA-BackComNet with QoS guarantee. The objective is to maximize the EE of users subject to the QoS requirements of users, the decoding order of successive interference cancellation and the reflection coefficient (RC) constraint, where the transmit power of the base station and the RC of the backscatter device are jointly optimized. To solve this non-convex problem, we develop a novel iteration algorithm by using Dinkelbach’s method and the quadratic transformation approach. Simulation results verify the effectiveness of the proposed scheme in improving the EE by comparing it with the other schemes.
TL;DR: In this paper, the authors consider an IRS-aided wireless communication system, where an active or passive RIS is employed to assist the communication between an access point and a user.
Abstract: In this letter, we consider an intelligent reflecting surface (IRS)-aided wireless communication system, where an active or passive IRS is employed to assist the communication between an access point and a user. First, we consider the downlink/uplink communication separately and optimize the IRS placement for rate maximization with an active or passive IRS. We show that given the same number of IRS reflecting elements, the active IRS should be deployed closer to the receiver with the IRS’s decreasing amplification power; while in contrast, the passive IRS should be deployed near either the transmitter or receiver. Moreover, with optimized IRS placement, the passive IRS is shown to outperform its active counterpart when the number of reflecting elements is sufficiently large and/or the active-IRS amplification power is too small. Next, we optimize the IRS placement for both active and passive IRSs to maximize the weighted sum-rate of uplink and downlink communications. We show that in this case, the passive IRS is more likely to achieve superior rate performance. This is because the optimal active-IRS placement needs to balance the rate performance in the uplink and downlink, while deploying the passive IRS near the transmitter or receiver is optimal regardless of the uplink or downlink.
TL;DR: A multi-objective optimization framework is introduced to investigate the fundamental trade-off between the data sum-rate maximization and the total harvested energy maximization, by jointly optimizing the energy/information beamforming vectors at the BS and the phase shifts at the IRS.
Abstract: In this letter, we study the resource allocation for a multiuser intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits energy and information signals simultaneously to multiple energy harvesting receivers (EHRs) and information decoding receivers (IDRs) assisted by an IRS. Under this setup, we introduce a multi-objective optimization (MOOP) framework to investigate the fundamental trade-off between the data sum-rate maximization and the total harvested energy maximization, by jointly optimizing the energy/information beamforming vectors at the BS and the phase shifts at the IRS. This MOOP problem is first converted to a single-objective optimization problem (SOOP) via the $\epsilon $ -constraint method and then solved by majorization minimization (MM) and inner approximation (IA) techniques. Simulation results unveil a non-trivial trade-off between the considered competing objectives, as well as the superior performance of the proposed scheme as compared to various baseline schemes.
TL;DR: In this paper, a new RIS-aided communication system, where multiple RISs assist in the communication between a multi-antenna base station (BS) and a remote single antenna user by multi-hop signal reflection, was proposed.
Abstract: Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop signal reflection. Specifically, by exploiting the line-of-sight (LoS) link between nearby IRSs, a multi-hop cascaded LoS link between the BS and user is established where a set of IRSs are selected to successively reflect the BS’s signal, so that the received signal power at the user is maximized. To tackle this new problem, we first present the closed-form solutions for the optimal active and cooperative passive beamforming at the BS and selected IRSs, respectively, for a given beam route. Then, we derive the end-to-end channel power, which unveils a fundamental trade-off in the optimal beam routing design between maximizing the multiplicative passive beamforming gain and minimizing the multi-reflection path loss. To reconcile this trade-off, we recast the IRS selection and beam routing problem as an equivalent shortest simple-path problem in graph theory and solve it optimally. Numerical results show significant performance gains of the proposed algorithm over benchmark schemes and also draw useful insights into the optimal beam routing design.
TL;DR: This letter proposes a fast channel estimation scheme with reduced OFDM symbol duration for arbitrary frequency-selective fading channels and proposes a new scheme based on the novel concept of sampling-wise IRS reflection variation.
Abstract: In this letter, we study efficient channel estimation for an intelligent reflecting surface (IRS)-assisted orthogonal frequency division multiplexing (OFDM) system to achieve minimum training time. First, a fast channel estimation scheme with reduced OFDM symbol duration is proposed for arbitrary frequency-selective fading channels. Next, under the typical condition that the IRS-user channel is line-of-sight (LoS) dominant, another fast channel estimation scheme based on the novel concept of sampling-wise IRS reflection variation is proposed. Moreover, the pilot signal and IRS training reflection pattern are jointly optimized for both proposed schemes. Finally, the proposed schemes are compared in terms of training time and channel estimation performance via simulations, as well as against benchmark schemes.
TL;DR: This letter studies the robust transmission design for a reconfigurable intelligent surface (RIS)-aided secure communication system in the presence of transceiver hardware impairments and adopts the alternate optimization method to iteratively optimize one set of variables while keeping the other set fixed.
Abstract: In practice, residual transceiver hardware impairments inevitably lead to distortion noise which causes the performance loss. In this letter, we study the robust transmission design for a reconfigurable intelligent surface (RIS)-aided secure communication system in the presence of transceiver hardware impairments. We aim for maximizing the secrecy rate while ensuring the transmit power constraint on the active beamforming at the base station and the unit-modulus constraint on the passive beamforming at the RIS. To address this problem, we adopt the alternate optimization method to iteratively optimize one set of variables while keeping the other set fixed. Specifically, the successive convex approximation (SCA) method is used to solve the active beamforming optimization subproblem, while the passive beamforming is obtained by using the semidefinite program (SDP) method. Numerical results illustrate that the proposed transmission design scheme is more robust to the hardware impairments than the conventional non-robust scheme that ignores the impact of the hardware impairments.
TL;DR: In this paper, the performance of RIS-aided massive MIMO systems with direct links is investigated, and the phase shifts of the RIS are designed based on the statistical channel state information (CSI).
Abstract: This letter investigates the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (mMIMO) systems with direct links, and the phase shifts of the RIS are designed based on the statistical channel state information (CSI). We first derive the closed-form expression of the uplink ergodic data rate. Then, based on the derived expression, we use the genetic algorithm (GA) to solve the sum data rate maximization problem. With low-complexity maximal-ratio combination (MRC) and low-overhead statistical CSI-based scheme, we validate that the RIS can bring significant performance gains to the traditional mMIMO systems.
TL;DR: This letter focuses on the problem of pilot assignment in cell-free massive MIMO systems and exploiting the well-known Hungarian algorithms, two procedures are proposed, one maximizing the system throughput and the other maximizing the fairness across users.
Abstract: This letter focuses on the problem of pilot assignment in cell-free massive MIMO systems. Exploiting the well-known Hungarian algorithms, two procedures are proposed, one maximizing the system throughput, and the other one maximizing the fairness across users. The algorithms operate based on the knowledge of large-scale fading coefficients as a proxy for the distances between users in the system, and take into account both the uplink and downlink performance. Numerical results show that the proposed pilot assignment algorithms are effective and outperform the many competing alternatives available in the literature.
TL;DR: The performance of reconfigurable intelligent surface (RIS)-aided wireless networks over Rician fading channels is considered, and new accurate closed-form approximations for several performance measures are derived, including the outage probability, average symbol error probability, and the channel capacity.
Abstract: We consider in this letter the performance of reconfigurable intelligent surface (RIS)-aided wireless networks over Rician fading channels. We derive new accurate closed-form approximations for several performance measures, including the outage probability, average symbol error probability (ASEP), and the channel capacity. Additionally, to get more insights into the system behavior, we derive asymptotic expression for the outage probability at high signal-to-noise ratio (SNR) values, and provide closed-form expressions for the system diversity order and coding gain. Findings show that the considered RIS scenario can provide a diversity order of $\frac {a+1}{2}$ , where ${a}$ is a function of the Rician channel ${K}$ -factor, Rician channel scale parameter $\boldsymbol{\Omega }$ and the number of reflecting elements ${N}$ .
TL;DR: In this article, the authors proposed a novel hybrid communication network that utilizes both a full-duplex (FD) Decode-and-Forward (DF) relay and an Intelligent Reflecting Surface (IRS) to support data transmission over wireless channels.
Abstract: In this work, we propose a novel hybrid communication network that utilizes both a Full-Duplex (FD) Decode-and-Forward (DF) relay and an Intelligent Reflecting Surface (IRS) to support data transmission over wireless channels. We design the reflecting coefficients at the IRS to maximize the minimum achievable rate of the two hops for the proposed hybrid network. To that end, we utilize a change-of-variables with Semi-Definite Relaxation (SDR) approach to overcome the non-concave objective function and the non-convex optimization constraints. Our results demonstrate that the proposed hybrid IRS with FD relay scheme is able to achieve a significant performance gain over both the hybrid IRS with Half-Duplex (HD) relay as well as the IRS-only scheme, given that the self-interference at the relay is sufficiently suppressed.
TL;DR: This letter addresses the spectrum sharing problem between multiple-input-multiple-output (MIMO) radar and multi-user MISO communication systems, where RIS is exploited to deal with the interference imposed by the base station.
Abstract: Reconfigurable intelligent surface (RIS) has been considered in wireless communication systems to improve spectral efficiency. This letter addresses the spectrum sharing problem between multiple-input-multiple-output (MIMO) radar and multi-user MISO communication systems, where RIS is exploited to deal with the interference imposed by the base station (BS). We aim to maximize the radar detection probability by jointly optimizing the BS transmit beamformer and RIS phase shift matrix, subject to the users’ signal-to-interference-plus-noise-ratio and power consumption constraints. Due to the coupled variables, the formulated problem is challenging to solve; hence, we convert it into a better tractable form and propose an alternating algorithm to handle the resulting problem. The simulation results validate the effectiveness of RIS in controlling interference and improving radar detection probability.
TL;DR: The capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs) shows that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when the mode error is low.
Abstract: This letter presents the capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs). In the considered system, some of the UAVs are equipped with an IRS panel that applies certain phase-shifts to the incident waves before being reflected to the receiving UAV. In contrast to existing work, this letter considers the effect of imperfect phase knowledge on the system capacity, where the phase error is modeled as a von Mises random variable with parameter $\kappa $ . Analytical results, corroborated by Monte Carlo simulations, show that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when $\kappa \geq $ 6.
TL;DR: In this paper, the minimum required number of phase quantization levels in order to achieve the full diversity order in RIS-assisted wireless communication systems was revealed, with the aid of an upper bound of the outage probability.
Abstract: Due to hardware limitations, the phase shifts of the reflecting elements of reconfigurable intelligent surfaces (RISs) need to be quantized into discrete values. This letter aims to unveil the minimum required number of phase quantization levels ${L}$ in order to achieve the full diversity order in RIS-assisted wireless communication systems. With the aid of an upper bound of the outage probability, we first prove that the full diversity order is achievable provided that ${L}$ is not less than three. If ${L}\,\,=$ 2, on the other hand, we prove that the achievable diversity order cannot exceed ( ${N}\,\,+$ 1)/2, where ${N}$ is the number of reflecting elements. This is obtained with the aid of a lower bound of the outage probability. Therefore, we prove that the minimum required value of ${L}$ for achieving the full diversity order is ${L}\,\,=$ 3. Simulation results verify the theoretical analysis and the impact of phase quantization levels on RIS-assisted communication systems.
TL;DR: This letter investigates optimizing the reflect beamforming of the IRS and the time allocation among the BS's power transfer and different user clusters' information transmission to maximize the throughput of the network, and proposes an efficient algorithm based on the block coordinate ascent, semidefinite relaxation, and sequential rank-one constraint relaxation techniques to solve the resultant problem.
Abstract: The high reflect beamforming gain of the intelligent reflecting surface (IRS) makes it appealing not only for wireless information transmission but also for wireless power transfer. In this letter, we consider an IRS-assisted wireless powered communication network, where a base station (BS) transmits energy to multiple users grouped into multiple clusters in the downlink, and the clustered users transmit information to the BS in the manner of hybrid non-orthogonal multiple access and time division multiple access in the uplink. We investigate optimizing the reflect beamforming of the IRS and the time allocation among the BS’s power transfer and different user clusters’ information transmission to maximize the throughput of the network, and we propose an efficient algorithm based on the block coordinate ascent, semidefinite relaxation, and sequential rank-one constraint relaxation techniques to solve the resultant problem. Simulation results have verified the effectiveness of the proposed algorithm and have shown the impact of user clustering setup on the throughput performance of the network.
TL;DR: In this article, the authors investigated the operation of an intelligent reflecting surface (IRS) under predictable receiver mobility and developed a continuous time system model for multipath channels and discussed the optimal IRS configuration with respect to received power, Doppler spread, and delay spread.
Abstract: The operation of an intelligent reflecting surface (IRS) under predictable receiver mobility is investigated. We develop a continuous time system model for multipath channels and discuss the optimal IRS configuration with respect to received power, Doppler spread, and delay spread. It is shown that the received power can be maximized without adding Doppler spread to the system. In a numerical case study, we show that an IRS having the size of just two large billboards can improve the link budget of ground to Low Earth Orbit (LEO) satellite links by up to 6dB. It also adds a second, almost equivalently strong, communication path that improves the link reliability.