Article

Stochastic Learning-Based Robust Beamforming Design for RIS-Aided Millimeter-Wave Systems in the Presence of Random Blockages

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  • Brunel University of London
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Abstract

A fundamental challenge for millimeter wave (mmWave) communications lies in its sensitivity to the presence of blockages, which impact the connectivity of the communication links and ultimately the reliability of the network. In this paper, we analyze a mmWave communication system assisted by multiple reconfigurable intelligent surface (RISs) for enhancing the network reliability and connectivity in the presence of random blockages. To enhance the robustness of beamforming in the presence of random blockages, we formulate a stochastic optimization problem based on the minimization of the sum outage probability. To tackle the proposed optimization problem, we introduce a low-complexity algorithm based on the stochastic block gradient descent method, which learns sensible blockage patterns without searching for all combinations of potentially blocked links. Numerical results confirm the performance benefits of the proposed algorithm in terms of outage probability and effective data rate.

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... With the aid of CoMP transmission, a stochastic learning approach was proposed to capture crucial blockage patterns, and a robust beamforming design was established to combat uncertain path blockages, e.g., [14], [15]. Similarly, a learning-based robust beamforming design was proposed for RISaided mmWave systems in the presence of random blockages [16]. ...
... In what follows, our first goal is to investigate the impact of link blockage ε k . To simulate random blockage events for the downlink, we adopt a probabilistic model [15], [16], by which each path undergoes a random and independent blockage. Specifically, we utilize the homogeneous Poisson process to emulate the statistical properties of blockage behavior of mmWave communication links between the BS and the MS. ...
... In Fig. 7, we proceed to evaluate the outage probability versus CSI uncertainty in our proposed framework by taking into account the effects of the beamwidth and compare the performance against the methods in [9] and [16]. In our experiment, we mainly consider two typical user access scenarios, namely the edge user and centric user. ...
Article
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Millimeter wave (mmWave) communications are sensitive to blockage over radio propagation paths. The emerging paradigm of reconfigurable intelligent surface (RIS) has the potential to overcome this issue by its ability to arbitrarily reflect the incident signals toward desired directions. This paper proposes a Neyman-Pearson (NP) criterion-based blockage-aware algorithm to improve communication resilience against blockage in mobile mmWave multiple input multiple output (MIMO) systems. By virtue of this pragmatic blockage-aware technique, we further propose an outage-constrained beamforming design for downlink mmWave MIMO transmission to achieve outage probability minimization and achievable rate maximization. To minimize the outage probability, a robust RIS beamformer with variant beamwidth is designed to combat uncertain channel state information (CSI). For the rate maximization problem, an accelerated projected gradient descent (PGD) algorithm is developed to solve the computational challenge of high-dimensional RIS phase-shift matrix (PSM) optimization. Particularly, we leverage a subspace constraint to reduce the scope of the projection operation and formulate a new Nesterov momentum acceleration scheme to speed up the convergence process of PGD. Extensive experiments confirm the effectiveness of the proposed blockage-aware approach, and the proposed accelerated PGD algorithm outperforms a number of representative baseline algorithms in terms of the achievable rate.
... In particular, a fully digital outage minimization (OutMin) beamforming was first presented in [28], where a sum-of-outage minimization problem was formulated and cast into an empirical risk minimization (ERM) problem, efficiently solved via a mini-batch stochastic gradient descent (MSGD) approach. The extension of the latter to a hybrid design was then proposed in [29], and the approach was modified in [30] to also exploit reflected intelligence surfaces (RISs), by employing a block mini-batch stochastic gradient descent (BMSGD) technique to design beamforming vectors and reflection coefficients jointly. ...
... A limitation of the aforementioned blockage-robust mitigation methods [28]- [30] is, however, that they all consider single carrier transmission over frequency flat channels, making them unsuitable to mmWave systems, which operate over much wider bandwidths than sub-6 [GHz] systems and are affected by frequency selectivity. While the effect of the frequency selectivity can be effectively mitigated by equalization over orthogonal frequency division multiplexing (OFDM) transmissions, conventional methods based on this approach exhibit high outage probabilities due to the per-carrier transmit power allocation that does not consider blockage probability and the distribution of the sum rate over subcarriers. ...
... In order to address this limitation, in [31], a BMSGDbased scheme for the joint design of OutMin fully digital beamformers and optimal transmit power allocation was proposed for multi-carrier OFDM mmWave MIMO systems, which was shown to successfully combat both path blockage and frequency selective effects of the channel. Still, the method proposed in [31] has two drawbacks; requiring a fully digital architecture and exhibiting a decrease in total system data rate the same as single carrier approaches [29], [30]. ...
Article
Full-text available
We propose a scheme for the concomitant design of hybrid beamforming and per-carrier transmit power allocation to mitigate the effect of random path blockages in coordinated multi-point (CoMP) systems using orthogonal frequency division multiplexing (OFDM) in millimeter-wave (mmWave) channels. In order to optimize both the beamformers and power allocation while dealing simultaneously with outage minimization and sum rate maximization (SRM) requirements, a regularized sum-of-outage minimization problem is formulated. The problem is then transformed into an empirical risk minimization (ERM) problem, solved via block stochastic learning and manifold optimization, with required learning rates derived and tuned to guarantee convergence. The method, which demands only a few radio frequency (RF) chains and relies only on knowledge of blockage probabilities, is shown via simulation results not only to outperform state-of-the-art (SotA) alternatives, but to actually achieve outage probabilities comparable to those a fully digital CoMP-SRM scheme with perfect knowledge of instantaneous blockages.
... The aforementioned contributions, however, consider only total throughput, such that quality of service (QoS) cannot be guaranteed, and assume that blockage occurs only on line-ofsight (LOS) paths, which is impractical for mmWave systems [25], [40]. In contrast, stochastic approaches for beamforming design aiming at guaranteeing QoS have been proposed in [41]- [43]. These considered the cooperative outage minimization (OutMin) beamforming schemes with predicted blockage probabilities that minimize the outage probability of the given users' target data rates. ...
... The extension of that approach to hybrid beamforming design was then obtained in [42] by following a block coordinate descent (BCD) framework. In [43], these stochastic approaches were applied to a reflected intelligence surface (RIS)-aided mmWave system, with the beamforming and reflection coefficient vectors updated based on the block mini-batch stochastic gradient descent (BMSGD). ...
... According to [24], it is experimentally confirmed that propagation paths are randomly blocked with a probability ranging from 20% to 60%. Therefore, similarly to [23], [38], [39], [41]- [43], we assume that blockage effects are modeled by random variables ω c b,u ∈ {0, 1} following the Bernoulli distribution with the mean p c b,u . Then, during the data transmission phase after the channel estimation, the actual channel between the b-th BS and u-th UE at the d-th delay tap can be expressed as ...
Article
Full-text available
We consider millimeter-wave (mmWave) orthogonal frequency division multiplexing (OFDM) systems subjected to random propagation path blockages and propose a new Coordinated multi-point (CoMP) transmission scheme that minimizes the outage probability of users with respect to given target data rates. To this end, a stochastic sum-outage-probability minimization problem is formulated for joint beamforming design, data rate allocation, and power allocation over subcarriers. In order to solve this problem efficiently, a block statistic learning approach is introduced using training data generated from a priori knowledge of path blockage probabilities. To initialize the stochastic learning solver, the novel initial beamforming is also proposed based on the upper bound of the original objective function, which improves convergence without tuning hyper-parameters. Numerical results confirm the effectiveness of the proposed block stochastic learning approach in terms of both convergence behavior and outage probability. Furthermore, these results confirm that the proposed approach with only blockage probabilities is comparable to the outage performance of a CoMP sum rate maximization (SRM) transmission scheme with perfect channel state information (CSI) and perfect knowledge of blockages.
... Tons of papers have studied and designed RIS-assisted wireless networks because of the great impact of utilizing RIS capabilities in enhancing faded channels and blocking problems. The research begins by investigating joint active and passive beamforming (JAPBF) between BS and single RIS and then upgraded to utilizing cooperation of passive beamforming between multi-RISs in different topologies, i.e., parallel, cascaded, and hybrid ways [13][14][15][16][17][18][19]. ...
... h H s,k = φ s l,n α l,n + β l,n , where Once we have reformulated h H s,k for the passive beamforming scenario, the objective function in (13) can be represented as a function of φ l,n as where δ 1 , δ 2 , …, δ K are the newly introduced complex auxiliary variables and δ = [δ 1 , δ 2 , . . . , δ K ] T is the auxiliary variable vector. ...
Article
Full-text available
Reconfigurable intelligent surface (RIS) is a groundbreaking technology that has a significant potential for sixth generation (6G) networks. Its unique capability to control wireless environments makes it an attractive option. However, the spatial diversity increased by assisting users with all deployed RISs, this investigation has two drawbacks the high complexity design, and the received signals by the far RISs are severely attenuated. Therefore, we propose a RIS selection strategy to select the proper RISs as a pre-stage before the joint beamforming between the base station (BS) and RISs to reduce the high complexity of joint beamforming optimization. Furthermore, the joint active and passive beamforming problem based on the selection is formulated. Hence, achieving spatial diversity by examining cooperation between passive beamforming of multi-hop RIS, leads to a challenging problem. To tackle this issue, we design an algorithm for the RIS selection scheme. Also, to relax the non-convexity of the proposed problem, we decouple the problem into solvable subproblems by utilizing the fractional programming (FP) and quadratic transform (QT) optimization methods. Simulation results have demonstrated through different user locations the effectiveness of the selection strategy in performance enhancement by 30% in the sum rate, besides an obvious reduction in the complexity cost than other techniques.
... x H x is x * = cν 1 , where c is an arbitrary non-zero constant and ν 1 is the eigen-vector corresponding to the largest eigen-value of Q. Thus, based on the relaxation and projection method of [35], [36], the optimal solution of (P3.a), denoted as ξ * , is ξ * = e jν1 . ...
... x H x is x * = c ν 1 , where c is an arbitrary non-zero constant and ν 1 is the eigen-vector corresponding to the largest eigen-value of Q. Thus, based on the relaxation and projection method of [35], [36], the optimal solution of (P3.b1), denoted as z * , is z * = e j ν1 . ...
Article
Full-text available
Reconfigurable holographic surfaces (RHSs) constitute a promising technique of supporting energy-efficient communications. In this paper, we formulate the energy efficiency maximization problem of the switch-controlled RHS-aided beamforming architecture by alternately optimizing the holographic beamformer at the RHS, the digital beamformer, the total transmit power and the power sharing ratio of each user. Specifically, to deal with this challenging non-convex optimization problem, we decouple it into three sub-problems. Firstly, the coefficients of RHS elements responsible for the holographic beamformer are optimized to maximize the sum of the eigen-channel gains of all users by our proposed low-complexity eigen-decomposition (ED) method. Then, the digital beamformer is designed by the singular value decomposition (SVD) method to support multi-user information transfer. Finally, the total transmit power and the power sharing ratio are alternately optimized, while considering the effect of transceiver hardware impairments (HWI). We theoretically derive the spectral efficiency and energy efficiency performance upper bound for the RHS-based beamforming architectures in the presence of HWIs. Our simulation results show that the switch-controlled RHS-aided beamforming architecture achieves higher energy efficiency than the conventional fully digital beamformer and the hybrid beamformer based on phase shift arrays (PSA). Moreover, considering the effect of HWI in the beamforming design can bring about further energy efficiency enhancements.
... Tons of papers have studied and designed RIS-assisted wireless networks because of the great impact of utilizing RIS capabilities in enhancing faded channels and blocking problems. The research begins by investigating joint active and passive beamforming (JAPBF) between BS and single RIS, then upgraded to utilizing cooperation of passive beamforming between multi-RISs in different topologies, i.e., parallel, cascaded and hybrid ways, [13]- [19]. ...
... Once we have reformulated , for the passive beamforming scenario, the objective function in (13) can be represented as a function of , as ...
Preprint
Full-text available
Reconfigurable intelligent surface (RIS) is a groundbreaking technology that has a significant potential for sixth generation (6G) networks. Its unique capability to control wireless environments makes it an attractive option. However, the spatial diversity increased by assisting users with all deployed RISs, this investigation has two drawbacks the high complexity design and the received signals by the far RISs are severely attenuated. Therefore, we propose a RIS selection strategy to select the proper RISs as a pre-stage before the joint beamforming between the base station (BS) and RISs to reduce the high complexity of joint beamforming optimization. Furthermore, the joint active and passive beamforming problem based on the selection is formulated. Hence, achieving spatial diversity by examining cooperation between passive beamforming of multi-hop RIS, leads to a challenging problem. To tackle this issue, we design an algorithm for the RIS selection scheme. Also, to relax the non-convexity of the proposed problem, we decouple the problem into solvable subproblems by utilizing the fractional programming (FP) and quadratic transform (QT) optimization methods. Simulation results have demonstrated through different user locations the effectiveness of the selection strategy in performance enhancement by 30% in the sum rate. Besides, an obvious reduction in the complexity cost than other techniques.
... And obtain a solution for the new formulated problem and then project the obtained solution onto the unit-modulus constraint S 1 . Accordingly, having the solution θ m of the relaxed problem, the final solution is θ ⋆ m = e j ϕ m , where ϕ m is the phase of θ m as applied in [47,48,49]. ...
... 48: Received power as a function of the angle of observation. The RIS alphabet is[8], the desired angle of reflection is 75 degrees, and the inter-distance is d = λ/8. ...
Thesis
Recently, the emergence of reconfigurable intelligent surface (RIS) has attracted heated attention from both industry and academia. An RIS is a planar surface that consists of a large number of low-cost passive reflecting elements. By carefully adjusting the phase shifts of the reflecting elements, an RIS can reshape the wireless environment for better communication. In general, this thesis provides contributions on: (i) the performance of RISs based on accurate and realistic electromagnetic reradiation models. Moreover, it provides some of optimization frameworks for enhancing the communication system performance on the following two use case: (i) To jointly improves the information rate and the amount of harvested power in a RIS-aided MISO downlink multiuser wireless network. (ii) enhancing spectral efficiency for large number of users located on cell edge or on the other side of the RIS by utilizing the intelligent omni-surfaces (IOSs).Chapter 1 introduces the challenges of fulfilling the requirements of of 6G networks, the concept of smart radio environments and RIS as it is one of the enabling technologies. In future communications, RIS is a key technique that will have potential applications which will achieve seamless connectivity and less energy consumption at the same time. Chapter 2 also introduces the state-of-art optimization techniques developed for RIS-aided systems. Firstly, it introduces the system models of RIS-aided MIMO systems and then investigates the reflection principle of RISs. In addition, it introduces the Optimization techniques challenges of RIS-assisted systems. Also, the proposed optimization techniques for designing the continuous and discrete phase shifts are presented in detail. Chapter 3 studies 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. In conclusion, our study shows that, due to design constraints, such as the need to use quantized reflection coefficients or the inherent interplay between the phase and the amplitude of the reflection coefficients, a RIS may reradiate power towards unwanted directions that depend on the intended and interfering electromagnetic waves. Chapter 4 considers the problem of simultaneously optimizing the information rate and the harvested power in a reconfigurable intelligent surface (RIS)-aided MISO downlink multiuser wireless network with simultaneous wireless information, and power transfer (SWIPT) is addressed. A practical algorithm is developed through an interplay of alternating optimization, sequential optimization, and pricing-based methods. Chapter 5 proposes an optimization algorithm that has a rapid convergence rate in a few iterations for maximizing the sum rate in IOS-aided MIMO broadcast channels, which can be exploited to serve the cell-edge user and enhance network coverage. This work's distinguishable feature lies in considering that the reflection and transmission coefficients of an IOS are tightly coupled. Finally, Chapter 6 summarizes the main findings of the thesis and discusses possible future directions that are worth investigating to unlock the full potential of RIS and bring it into practice.
... Considering the distinct required SINR of UEs, the authors in [152] analyzed the maximization process of weighted sum power received by energy RXs by joint optimization of transmit and passive beamforming along with AO-assisted procedure in RIS-aided SWIPT network. Besides, the maximization procedure of the smallest received energy among the power receiving devices was proposed in [153][154][155][156][157][158][159]. Additionally, several investigations found RIS to enhance EE in wireless networks [154], [155]. ...
... In [160], the authors investigated the total computation bits maximization problem for RIS-enhanced wireless powered MEC networks, by jointly optimizing the downlink/uplink phase beamforming of RIS, transmission power and time slot assignment used for wireless energy transfer and task offloading, and local computing frequencies of IoT devices. On the other hand, depending on the requirement of energy picking by every UE, authors in [157] explored the boosting process of weighted sum rate in RIS-aided SWIPT MIMO network where a block coordinate descent (BCD)-assisted procedure finds the Karush-Kuhn-Tucker (KKT) stationary spot. Moreover, a multi-RISassisted SWIPT system was presented in [154], in which the transmit power reduction increases the QoS of both the energy user (EU) and information user (IU). ...
Article
Sixth generation (6G) internet of things (IoT) networks will modernize the applications and satisfy user demands through implementing smart and automated systems. Intelligence-based infrastructure, also called reconfigurable intelligent surfaces (RISs), have been introduced as a potential technology striving to improve system performance in terms of data rate, latency, reliability, availability, and connectivity. A huge amount of cost-effective passive components are included in RISs to interact with the impinging electromagnetic waves in a smart way. However, there are still some challenges in RIS system, such as finding the optimal configurations for a large number of RIS components. In this paper, we first provide a complete outline of the advancement of RISs along with machine learning (ML) algorithms and overview the working regulations as well as spectrum allocation in intelligent IoT systems. Also, we discuss the integration of different ML techniques in the context of RIS, including deep reinforcement learning (DRL), federated learning (FL), and FL-deep deterministic policy gradient (FL-DDPG) techniques which are utilized to design the radio propagation atmosphere without using pilot signals or channel state information (CSI). Additionally, in dynamic intelligent IoT networks, the application of existing integrated ML solutions to technical issues like user movement and random variations of wireless channels are surveyed. Finally, we present the main challenges and future directions in integrating RISs and other prominent methods to be applied in upcoming IoT networks.
... Considering the distinct required SINR of UEs, the authors in [152] analyzed the maximization process of weighted sum power received by energy RXs by joint optimization of transmit and passive beamforming along with AO-assisted procedure in RIS-aided SWIPT network. Besides, the maximization procedure of the smallest received energy among the power receiving devices was proposed in [153][154][155][156][157][158][159]. Additionally, several investigations found RIS to enhance EE in wireless networks [154], [155]. ...
... In [160], the authors investigated the total computation bits maximization problem for RIS-enhanced wireless powered MEC networks, by jointly optimizing the downlink/uplink phase beamforming of RIS, transmission power and time slot assignment used for wireless energy transfer and task offloading, and local computing frequencies of IoT devices. On the other hand, depending on the requirement of energy picking by every UE, authors in [157] explored the boosting process of weighted sum rate in RIS-aided SWIPT MIMO network where a block coordinate descent (BCD)-assisted procedure finds the Karush-Kuhn-Tucker (KKT) stationary spot. Moreover, a multi-RISassisted SWIPT system was presented in [154], in which the transmit power reduction increases the QoS of both the energy user (EU) and information user (IU). ...
Preprint
Full-text available
Sixth generation (6G) internet of things (IoT) networks will modernize the applications and satisfy user demands through implementing smart and automated systems. Intelligence-based infrastructure, also called reconfigurable intelligent surfaces (RISs), have been introduced as a potential technology striving to improve system performance in terms of data rate, latency, reliability, availability, and connectivity. A huge amount of cost-effective passive components are included in RISs to interact with the impinging electromagnetic waves in a smart way. However, there are still some challenges in RIS system, such as finding the optimal configurations for a large number of RIS components. In this paper, we first provide a complete outline of the advancement of RISs along with machine learning (ML) algorithms and overview the working regulations as well as spectrum allocation in intelligent IoT systems. Also, we discuss the integration of different ML techniques in the context of RIS, including deep reinforcement learning (DRL), federated learning (FL), and FL-deep deterministic policy gradient (FL-DDPG) techniques which are utilized to design the radio propagation atmosphere without using pilot signals or channel state information (CSI). Additionally, in dynamic intelligent IoT networks, the application of existing integrated ML solutions to technical issues like user movement and random variations of wireless channels are surveyed. Finally, we present the main challenges and future directions in integrating RISs and other prominent methods to be applied in upcoming IoT networks. <br
... In [32], the authors consider the blockage effect on the RIS-UE link under different blocking probabilities. Moreover, the authors in [37], [39] were just content with considering random blockage occurrences in the RIS aided system while designing the active and passive beamforming (A-PBF). In these works, no practical blockage model was assumed, and the blockage probability has not been studied versus network parameters such as blocker densities, BSs/RISs density. ...
Article
Full-text available
Recently, reconfigurable intelligent surfaces (RISs) aided millimeter wave (mmWave) and terahertz (THz) communication systems have attracted interest as enablers for 5G and beyond networks. Although the static blockers impact can be eliminated by the optimal deployment of RISs, the effect of dynamic and self-blockage can only be reduced. First, due to mobile blockers and the user equipment (UE) itself, the RIS-UEs links can be blocked as well as the base station (BS)-UEs links. Second, in dense environments, all links to the UE can be blocked simultaneously causing a low received power. Furthermore, the dynamic blockers frequent interruptions and duration of blockages have a vital impact on the UE quality of service (QoS). Consequently, to tackle these points, in this paper, we derive an analytical dynamic blockage model to deduce various blockage metrics, i.e., blockage probability, frequency, and duration, in RISs aided systems considering all BSs-UE and RISs-UE links are not exposed to static or self-blocking. Moreover, we discuss the minimum required BSs/RISs density to guarantee UE QoS demands, e.g., link reliability and end-to-end latency, for beyond 5G network applications. Furthermore, we study the effects of the network specifications, e.g., BSs and RISs heights, communication range, and blockers density, on the required BSs/RISs density. Additionally, based on simulation analysis, we investigate the network performance, considering the blockage, in terms of spectral efficiency and energy efficiency. Our results prove that the RISs aided networks can be designed to satisfy the UE QoS requirements for serving different applications.
... A joint framework for power allocation and RIM PBF optimization is introduced in [115], wherein the element-wise Karush-Kuhn-Tucker optimal conditions are used to decrease the computational complexity. In [116], the authors investigate mmWave communications assisted by RIMs based on block stochastic gradient descent algorithm, aiming to optimize the hybrid analog-digital beamforming at the BS and the PBF at the RIMs. In [117], a joint collaborative and passive beamforming design strategy based on a penalty dual decomposition algorithm is presented to maximize network lifespan in RIM-assisted wireless sensor networks. ...
Article
Full-text available
Wireless networks are increasingly relying on machine learning (ML) paradigms to provide various services at the user level. Yet, it remains impractical for users to offload their collected data set to a cloud server for centrally training their local ML model. Federated learning (FL), which aims to collaboratively train a global ML model by leveraging the distributed wireless computation resources across users without exchanging their local information, is therefore deemed as a promising solution for enabling intelligent wireless networks in the data-driven society of the future. Recently, reconfigurable intelligent metasurfaces (RIMs) have emerged as a revolutionary technology, offering a controllable means for increasing signal diversity and reshaping transmission channels, without implementation constraints traditionally associated with multi-antenna systems. In this paper, we present a comprehensive survey of recent works on the applications of FL to RIM-aided communications. We first review the fundamental basis of FL with an emphasis on distributed learning mechanisms, as well as the operating principles of RIMs, including tuning mechanisms, operation modes, and deployment options. We then proceed with an in-depth survey of literature on FL-based approaches recently proposed for the solution of three key interrelated problems in RIM-aided wireless networks, namely: channel estimation (CE), passive beamforming (PBF) and resource allocation (RA). In each case, we illustrate the discussion by introducing an expanded FL (EFL) framework in which only a subset of active users partake in the distributed training process, thereby allowing to reduce transmission overhead. Lastly, we discuss some current challenges and promising research avenues for leveraging the full potential of FL in future RIM-aided extremely large-scale multiple-input-multiple-output (XL-MIMO) networks.
... such that ‚ ƒ I @L@ @LM is known as a spreading factor [19]. ...
Conference Paper
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We investigate the use of reconfigurable intelligent surfaces (RISs) in wireless networks to maximize the sum secrecy rate (i.e., the sum maximum rate that can be communicated under perfect secrecy). Specifically, we focus on a network that utilizes RIS-assisted unmanned aerial vehicles (UAVs) under imperfect channel state information (CSI). Our objective is to maximize the sum secrecy rate while dealing with the presence of multiple eavesdroppers. To achieve this, we jointly optimize the active (UAV) and passive (RIS) beamforming together with the UAV's trajectories. The formulated problem is non-convex due to the coupling of CSI with the maneuverability of the UAV. To overcome this challenge, we propose a policy-based deep reinforcement learning (DRL) approach that solves the non-convex optimization problem in a centralized fashion. Finally, simulation results show that our proposed approach significantly improves average sum secrecy rates over conventional approaches.
... The authors of [23] presented a distributed multiple RIS to support multiple users as a solution for constructing higherrank channels with high spatial multiplexing gain. To improve beamforming robustness in the presence of obstructions, the authors of [24] proposed a low complexity technique based on the stochastic block gradient descent method as a solution for minimizing the sum outage probability for the parallel topology of RISs. The authors in [25] proposed a large-scale RIS pre-assignment (LSRPA) approach in which user equipment (UE) and obstacle position and speed knowledge are combined with large-scale channel parameters to forecast and prioritize the RIS of interest among several RIS. ...
Article
Full-text available
Reconfigurable intelligent surface (RIS) is regarded as one of the main enablers in the context of 6G wireless communications. It converts the conventionally uncontrolled wireless channel into a programmed channel. The current interest in these surfaces is extended from just exploring the capabilities of single RIS to further exploring opportunities of employing multiple RIS cooperatively for enhancing network coverage and capacity. Unfortunately, almost all current work of multiple RIS-assisted networks are limited to either cascade or parallel topologies without regarding the most proper distribution according to the corresponding channel qualities and mutual orientations. So, in this paper, we are aiming to gain both benefits of cascaded and parallel topologies through a hybrid RIS networking structure. While cascade topology minimizes path loss and enhances multiplicative gain, the parallel topology is exploited for enriching scattering signatures in the interested region (cluster). First, cascaded grouping is resolved based on consecutive channel qualities through optimal routing technique. Then, a joint active and passive beamforming (JAPBF) problem is assumed over the grouped parallel routes. The spatial diversity problem is formulated as fractional programming (FP) optimization problem. The superiority of the proposed hybrid network is demonstrated through the performed simulation results represented in maximizing the overall achievable sum rate and exploring the sensitivity to location shift due to receiver mobility.
... Even though the proposed approach is independent of a specific channel model, in this evaluation we adopt a clustered geometric channel [35], that is commonly assumed in mmWave and sub-THz literature [36] [37]. In the case of the channels between the transmitter, RIS and receiver, we consider that the RIS panels were properly located so that they consist of a LOS and a non-line-of- ...
Article
Full-text available
In recent years there has been a growing interest in reconfigurable intelligent surfaces (RISs) as enablers for the realization of smart radio propagation environments which can provide performance improvements with low energy consumption in future wireless networks. However, to reap the potential gains of RIS it is crucial to jointly design both the transmit precoder and the phases of the RIS elements. Within this context, in this paper we study the use of multiple RIS panels in a parallel or multi-hop configuration with the aim of assisting a multi-stream multiple-input multiple-output (MIMO) communication. To solve the nonconvex joint optimization problem of the precoder and RIS elements targeted at maximizing the achievable rate, we propose a novel iterative algorithm based on the monotone accelerated proximal gradient (mAPG) method which includes an extrapolation step for improving the convergence speed and monitoring variables for ensuring sufficient descent of the algorithm. Based on the sufficient descent property we then present a detailed convergence analysis of the algorithm which includes expressions for the step size. Simulation results in different scenarios show that the use of multiple RIS panels combined with the proposed algorithm can be an effective solution for improving the achievable rates.
... Our channel model follows the idea of 3D SV channel model presented in [17][18]. Let the channel gain from UAV to RIS, from UAV to -th wiretapper, from UAV to -th users, from RIS to -th users and from RIS to -th wiretappers are represented as ∈ ℂ × , , ∈ ℂ × , , ∈ ℂ × , , ∈ ℂ × , and , ∈ ℂ × , respectively. ...
Conference Paper
Full-text available
This paper investigates the physical layer security (PLS) issue in reconfigurable intelligent surface (RIS) aided millimeter-wave rotary-wing unmanned aerial vehicle (UAV) communications under the presence of multiple eavesdroppers and imperfect channel state information (CSI). The goal is to maximize the worst-case secrecy energy efficiency (SEE) of UAV via a joint optimization of flight trajectory, UAV active beamforming and RIS passive beamforming. By interacting with the dynamically changing UAV environment, real-time decision making per time slot is possible via deep reinforcement learning (DRL). To decouple the continuous optimization variables, we introduce a twin twin-delayed deep deterministic policy gradient (TTD3) to maximize the expected cumulative reward, which is linked to SEE enhancement. Simulation results confirm that the proposed method achieves greater secrecy energy savings than the traditional twin-deep deterministic policy gradient DRL (TDDRL)-based method. Code is provided in https://github.com/yjwong1999/Twin-TD3
... Authors in [6] give some investigation about this point considering different blockage probabilities in their study area and assuming RIS-UE can be blocked, but they do not study the source of this blockage with a practical scenario, i.e., adapting blockage density or specific blockage models. Also, the authors in [9], [10] consider random blockage occurrence while designing beamforming for RIS aided communication system. To best of our knowledge, almost all related works, that study the human blockage effect, assumed the occurrence of blockage only between TX and RX, however, virtual RIS-UE links can be blocked. ...
... From a radio access perspective, the mmWave bands (30 GHz to 300 GHz) represent a good fit to face the aforementioned challenges with higher offered data rates (Gbps). However, these communications generally suffer from high path loss and unexpected blockages [6]. To this end, beamforming (BF) is used to enable highly directional communications. ...
Preprint
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Wireless traffic is exploding, due to the myriad of new connections and the exchange of capillary data at the edge of the networks to operate real-time processing and decision making. The latter especially affects the uplink traffic, which will grow in 6G and beyond networks, calling for new optimization metrics that include energy, service delay, and electromagnetic field (EMF) exposure (EMFE). To this end, reconfigurable intelligent surfaces (RISs) represent a promising solution to mitigate the EMFE, thanks to their ability of shaping and manipulating the impinging electromagnetic waves. In line with this vision, this paper proposes an online adaptive method to mitigate the EMFE under end-to-end delay constraints of a computation offloading service, in the context of RIS and multi-access edge computing (MEC)-aided wireless networks. The goal is to minimize the long-term average of the EMF human exposure under such constraints, investigating the advantages of RISs towards blue (i.e. low EMFE) communications. A multiple-input multiple-output (MIMO) system is investigated as part of the visions towards 6G. Focusing on a typical scenario of computation offloading, the method jointly and adaptively optimizes user precoding, transmit power, RIS reflectivity parameters, and receiver combiner, with theoretical guarantees on the desired long-term performance. Besides the theoretical results, numerical simulations assess the performance of the proposed algorithm, when exploiting accurate antenna patterns, thus showing the advantage of the RIS and that of our method, compared to benchmark solutions.
... Due to these attractive benefits, RISs can be deployed to increase network capacity, improve transmission reliability [10], reduce transmit power [11], and enlarge wireless coverage [12]. RISs can also bring gains to various emerging systems, such as RIS-aided massive MIMO systems [13], non-orthogonal multiple access (NOMA) networks [14], secure communication systems [15], device to device (D2D) communications [16], and millimeter-wave systems [17]. All these studies provide insightful analysis on the improved performance while exhibiting lower cost and higher efficiency than existing systems. ...
Preprint
This paper investigates the performance of two-timescale transmission design for uplink reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems. We consider the Rician channel model and design the passive beamforming of RISs based on the long-time statistical channel state information (CSI), while the maximum ratio combining (MRC) technique is utilized to design the active beamforming of base stations (BSs) based on the instantaneous overall channels, which are the superposition of the direct and RIS-reflected channels. Firstly, we derive the closed-form expressions of uplink achievable rate for arbitrary numbers of BS antennas and RIS reflecting elements. Relying on the derived expressions, we theoretically analyze the benefits of RIS-aided cell-free mMIMO systems and draw explicit insights. Then, based on closed-form expressions under statistical CSI, we maximize the sum user rate and the minimum user rate by optimizing the phase shifts of the RISs based on the genetic algorithm (GA). Finally, the numerical results demonstrate the feasibility and the benefits of deploying large-size RISs into conventional cell-free mMIMO systems. Besides, our results validate the effectiveness of the proposed two-timescale scheme in the RIS-aided cell-free mMIMO systems.
... An RIS is a planar array consisting of multiple low-cost reflecting elements which steers the incident signal by adjusting the phase shift and amplitude [5]. Owing to this ability, RISs can reconfigure the wireless channel to facilitate information transmission and the performance of mmWave communications can be significantly enhanced by deploying RISs on the exterior walls of buildings [6]. ...
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p>In this paper, a reconfigurable intelligent surfaces (RISs)-aided millimeter wave (mmWave) uplink (UL) rate-splitting multiple access (RSMA) system is investigated which targets to achieve better rate performance and enhanced coverage capability for multiple users. The considered UL RSMA model splits the rate for each user by dividing their message into multiple parts and hence exploits all the necessary degrees of freedom to achieve maximum capacity region and high user fairness. In particular, we focus on the sum-rate maximization for considered UL RSMA system subject to joint optimization of power allocation to the UL users and beamforming design, i.e., active receive beamforming at the base-station (BS) and passive beamforming at multiple RISs. To efficiently mitigate high inter-node interference in multi-user scenario, we first provided a low-complex user pairing scheme based on k-means clustering and then develop an effective low-cost alternating optimization framework to solve the joint optimization problem sub-optimally by decoupling the problem into different sub-problems of power allocation and beamforming design. Specifically, the sub-problems of power allocation and beamforming design are solved using successive convex approximation, Riemannian manifold and fractional programming techniques. Later, the unified solution based on block coordinate descent (BCD) algorithm is proposed. Extensive numerical simulations validate that the user-clustering effectively significantly improves the performance gain and the considered RSMA system outperforms the conventional multiple schemes in terms rate and user-fairness. Also, the exploitation of spatial correlation among each RIS elements i.e., non-diagonal phase-matrices at each RIS achieve better performance that conventional diagonal phase-matrices setting.</p
... An RIS is a planar array consisting of multiple low-cost reflecting elements which steers the incident signal by adjusting the phase shift and amplitude [5]. Owing to this ability, RISs can reconfigure the wireless channel to facilitate information transmission and the performance of mmWave communications can be significantly enhanced by deploying RISs on the exterior walls of buildings [6]. ...
Preprint
Full-text available
p>In this paper, a reconfigurable intelligent surfaces (RISs)-aided millimeter wave (mmWave) uplink (UL) rate-splitting multiple access (RSMA) system is investigated which targets to achieve better rate performance and enhanced coverage capability for multiple users. The considered UL RSMA model splits the rate for each user by dividing their message into multiple parts and hence exploits all the necessary degrees of freedom to achieve maximum capacity region and high user fairness. In particular, we focus on the sum-rate maximization for considered UL RSMA system subject to joint optimization of power allocation to the UL users and beamforming design, i.e., active receive beamforming at the base-station (BS) and passive beamforming at multiple RISs. To efficiently mitigate high inter-node interference in multi-user scenario, we first provided a low-complex user pairing scheme based on k-means clustering and then develop an effective low-cost alternating optimization framework to solve the joint optimization problem sub-optimally by decoupling the problem into different sub-problems of power allocation and beamforming design. Specifically, the sub-problems of power allocation and beamforming design are solved using successive convex approximation, Riemannian manifold and fractional programming techniques. Later, the unified solution based on block coordinate descent (BCD) algorithm is proposed. Extensive numerical simulations validate that the user-clustering effectively significantly improves the performance gain and the considered RSMA system outperforms the conventional multiple schemes in terms rate and user-fairness. Also, the exploitation of spatial correlation among each RIS elements i.e., non-diagonal phase-matrices at each RIS achieve better performance that conventional diagonal phase-matrices setting.</p
... An RIS is a planar array consisting of multiple low-cost reflecting elements which steers the incident signal by adjusting the phase shift and amplitude [5]. Owing to this ability, RISs can reconfigure the wireless channel to facilitate information transmission and the performance of mmWave communications can be significantly enhanced by deploying RISs on the exterior walls of buildings [6]. ...
Preprint
Full-text available
In this paper, a reconfigurable intelligent surfaces (RISs)-aided millimeter wave (mmWave) uplink (UL) rate-splitting multiple access (RSMA) system is investigated which targets to achieve better rate performance and enhanced coverage capability for multiple users. The considered UL RSMA model splits the rate for each user by dividing their message into multiple parts and hence exploits all the necessary degrees of freedom to achieve maximum capacity region and high user fairness. In particular, we focus on the sum-rate maximization for considered UL RSMA system subject to joint optimization of power allocation to the UL users and beamforming design, i.e., active receive beamforming at the base-station (BS) and passive beamforming at multiple RISs. To efficiently mitigate high inter-node interference in multi-user scenario, we first provided a low-complex user pairing scheme based on k-means clustering and then develop an effective low-cost alternating optimization framework to solve the joint optimization problem sub-optimally by decoupling the problem into different sub-problems of power allocation and beamforming design. Specifically, the sub-problems of power allocation and beamforming design are solved using successive convex approximation, Riemannian manifold and fractional programming techniques. Later, the unified solution based on block coordinate descent (BCD) algorithm is proposed. Extensive numerical simulations validate that the user-clustering effectively significantly improves the performance gain and the considered RSMA system outperforms the conventional multiple schemes in terms rate and user-fairness. Also, the exploitation of spatial correlation among each RIS elements i.e., non-diagonal phase-matrices at each RIS achieve better performance that conventional diagonal phase-matrices setting.
... The mmWave RIS have appeared as a solution for mobile operators, since they ensure high system reliability and user connectivity in a dense user scenario (wheremany potential blockers exist). The use of RIS is anticipated to alleviate the high-power consumption and complexity problems in 5G networks and reduce the interference resulting from network densification [23]. ...
Conference Paper
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Human blockage is one of the key challenges that limit the ability of mm Wave communications to provide ultra-high data rate and ultra-low latency links, thus severely reducing the quality-of-service (QoS) experienced by the users. In this paper, we present the most common human body blockage models, which are used in blockage analysis to predict the level of attenuation caused by the human body to mm Wave signals. Moreover, the main parameters of human blockage which affect the received signal are discussed, while the effect of blockage on the received signal and network coverage is analyzed. Finally, we provide insights to potential solutions that overcome human blockage, in order to further improve the overall performance of mm Wave communications.
... (1) Perfect instantaneous CSI: Most of the existing works have considered transmission design based on the assumption that the instantaneous CSI is perfectly available. Based on this assumption, the performance gains provided by introducing an RIS in various wireless applications have been investigated, such as mmWave/terahertz systems [84], [89], [142]- [145], multicell systems [101], [146], [147], physical layer security systems [83], [87], [88], [97], [98], [148], [149], simultaneous wireless information and power transfer (SWIPT) [99], [108], [113], [150]- [154], mobile edge computing networks [74], [111], [155]- [160], multicast networks [96], [161], cognitive radio networks [138], [162], [163], non-orthogonal multiple access [90], [92], [110], [112], [164]- [169], two-way communications [85], [100], and full-duplex (FD) communication [170]. In these works, the AO method was adopted to alternately optimize the beamforming vectors at the BS and the phase shifts at the RIS, and the phase shift optimization problem was addressed using the algorithms summarized in Subsection III-A. ...
Article
In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes. However, the improvements through applying such schemes operating only at two endpoints (i.e., transmitter and receiver) are limited even after five generations of wireless systems. Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) have emerged as a new and promising technology that can configure the wireless environment in a favorable manner by properly tuning the phase shifts of a large number of quasi passive and low-cost reflecting elements, thus standing out as a promising candidate technology for the next/sixth-generation (6G) wireless system. However, to reap the performance benefits promised by RIS/IRS, efficient signal processing techniques are crucial, for a variety of purposes such as channel estimation, transmission design, radio localization, and so on. In this paper, we provide a comprehensive overview of recent advances on RIS/IRS-aided wireless systems from the signal processing perspective.We also highlight promising research directions that are worthy of investigation in the future.
... Even though the proposed approach is independent of a specific channel model, in this evaluation we adopt a clustered geometric channel [29], that is commonly assumed in mmWave [30] and sub-THz literature [31]. In the case of the channels between the transmitter, RIS and receiver, we consider that the RIS panels were properly located so that they consist of a LOS and ...
Preprint
In recent years there has been a growing interest in reconfigurable intelligent surfaces (RISs) as enablers for the realization of smart radio propagation environments which can provide performance improvements with low energy consumption in future wireless networks. However, to reap the potential gains of RIS it is crucial to jointly design both the transmit precoder and the phases of the RIS elements. Within this context, in this paper we study the use of multiple RIS panels in a parallel or multi-hop configuration with the aim of assisting a multi-stream multiple-input multiple-output (MIMO) communication. To solve the nonconvex joint optimization problem of the precoder and RIS elements targeted at maximizing the achievable rate, we propose an iterative algorithm based on the monotone accelerated proximal gradient (mAPG) method which includes an extrapolation step for improving the convergence speed and monitoring variables for ensuring sufficient descent of the algorithm. Based on the sufficient descent property we then present a detailed convergence analysis of the algorithm which includes expressions for the step size. Simulation results in different scenarios show that, besides being effective, the proposed approach can often achieve higher rates than other benchmarked schemes.
Article
For wireless communication, the impact of blockage and propagation losses poses significant challenges to robust channel establishment. Reconfigurable Intelligent Surfaces (RIS) have been proposed as a promising technology for mitigating the coverage limitations inherent in many microwave and millimeter-wave wireless applications. However, wireless links facilitated by RIS are also susceptible to detrimental effects from blockages. In this paper, we present a spatial phase shift distribution (SPSD) method that alleviates adverse effects caused by blockages near RIS, exemplified for mmWave wireless scenarios. The proposed method refines the SPSD by accounting for distortions caused by blockages. This is achieved by modifying the conventional beamforming formula, which typically considers only the beam steering phase distribution between the incident wave and the desired direction. Through numerical simulations and by fabricating an RIS prototype for experimental validation, we demonstrate that the proposed method restores an average signal strength gain of approximately 3.5 dB in various scenarios, compared to traditional beamforming techniques in the presence of blockages. The proposed method can be used to optimize the transmit power of communication systems using RIS or to enhance the signal-to-noise ratio.
Article
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Multifunction phased array radars (MPARs) exploit the intrinsic flexibility of their active electronically steered array (ESA) to perform, at the same time, a multitude of operations, such as search, tracking, fire control, classification, and communications. This paper aims at addressing the MPAR resource allocation so as to satisfy the quality of service (QoS) demanded by both line of sight (LOS) and reflective intelligent surfaces (RIS)-aided non line of sight (NLOS) search operations along with communications tasks. To this end, the ranges at which the cumulative detection probability and the channel capacity per bandwidth reach a desired value are introduced as task quality metrics for the search and communication functions, respectively. Then, to quantify the satisfaction level of each task, for each of them a bespoke utility function is defined to map the associated quality metric into the corresponding perceived utility. Hence, assigning different priority weights to each task, the resource allocation problem, in terms of radar power aperture (PAP) specification, is formulated as a constrained optimization problem whose solution optimizes the global radar QoS. Several simulations are conducted in scenarios of practical interest to prove the effectiveness of the approach.
Article
This paper presents an efficient channel estimation algorithm for multi-user reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) systems. In this paper, the concept of low rank matrix completion (LRMC) is exploited to reduce beam training overhead for channel estimation. The proposed beam training samples part of each channel matrix in a special pattern that is suitable for LRMC with less beam training overhead. Then, the beam training is followed by multi-user channel estimation. For computationally efficient channel estimation, the proposed algorithm exploits the property that all the channel matrices share the same low-rank subspace in multi-user RIS-aided systems. The shared subspace is derived by combining candidate subspaces, which are estimated by fast alternating least squares (FALS) from partially observed channels. With the shared subspace, all the missing entries of channels are recovered via computationally efficient linear estimation. The simulations and complexity analysis demonstrate that the proposed algorithm shows a superior accuracy-complexity trade-off compared to existing works.
Article
In this paper, we propose location-aware beam training and multi-dimensional atomic norm minimization (ANM)-based channel estimation for reconfigurable intelligent surface (RIS)-aided millimeter-wave systems. The use of both location information and RIS beamwidth adaptation allows a significant reduction of beam training overhead. However, considering a trade-off between accuracy and beam training overhead, this may induce inaccurate channel estimation. Nevertheless, superior channel estimation performance is achieved by multi-dimensional ANM techniques, which have been shown to be effective in capturing cascaded structures such as the channel in RIS-aided systems. In the proposed work, a cascade of BS-to-RIS channel and RIS-to-BS channel is represented as a linear combination of either steering vectors, 2D steering vectors, or 3D steering vectors, and ANM with appropriate dimension is applied to estimate the channel. From simulation results, it has been demonstrated that location-aware channel estimation via 2D ANM and 3D ANM achieves excellent estimation accuracy along with a reduced beam training overhead.
Article
This paper investigates the performance of a two-timescale transmission design for uplink reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems. We consider the Rician channel model and design the passive beamforming of RISs based on the long-time statistical channel state information (CSI), while the central processing unit (CPU) utilizes the maximum ratio combining (MRC) technology to perform fully centralized processing based on the instantaneous overall channel, which is the superposition of the direct and RIS-reflected channels. Firstly, we derive the closed-form approximate expression of the uplink achievable rate for arbitrary numbers of access point (AP) antennas and RIS reflecting elements, which can be used to obtain energy efficiency through the proposed total power model. Relying on the derived expressions, we theoretically analyze the impact of important system parameters on the rate and draw explicit insights into the benefits of RISs. Then, based on the rate expression under statistical CSI, we optimize the phase shifts of RISs by using the genetic algorithm (GA) to maximize the sum rate and minimum rate of users, respectively. Finally, the numerical results demonstrate the correctness of our expressions and the benefits of deploying large-size RISs into cell-free mMIMO systems. Also, we investigate the optimality and convergence behaviors of the GA to verify its effectiveness. To give a more beneficial analysis, we present numerical results to show the high energy efficiency of the system with the help of RISs. Besides, our results have revealed the benefits of distributed deployment of APs and RISs in the RIS-aided mMIMO system with cell-free networks.
Article
This study proposes a joint design approach for hybrid beamforming and reflecting beamforming in an intelligent reflecting surface (IRS)-assisted millimeter-wave massive multiuser multiple-input single-output system. The goal is to maximize energy efficiency using energy-and hardware-efficient hybrid beamforming architectures at the base station and low-resolution (e.g., 1–2 bits) phase shifters at the IRS. However, the problem of maximizing energy efficiency is complicated by the high coupling of design variables. To address this, we use a zero-force (ZF) beamforming technique as the digital component of hybrid beamforming and develop a probability learning algorithm based on a cross-entropy optimization (CEO) framework to determine the weights of the analog part of hybrid beamforming as well as IRS phase shifts simultaneously. Additionally, we seek to maximize spatial reuse benefits by increasing the size of the IRS while selecting only a limited number of IRS elements to improve spectral and energy efficiency while minimizing power consumption. This involves joint optimization of hybrid beamforming, IRS element selection, and phase shifts associated with the chosen IRS elements. Solving this problem is challenging, but the proposed ZF-assisted CEO algorithm can still be applied with slight modifications. Simulation results demonstrate that our algorithms achieve significantly better energy efficiency than competitors while maintaining reasonable spectral efficiency.
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Unmanned aerial vehicles (UAVs) can support low-cost, highly mobile communications while making it possible to establish dedicated terrestrial networks. To overcome the pointing error (PE) and beam misalignment of millimeter-wave large-scale multiple-input multiple-output/free-space optics (MIMO/FSO) caused by UAV jitter, a millimeter-wave massive MIMO/FSO hybrid beamforming method based on tensor train decomposition is proposed. This approach is used for reconfigurable intelligent surface (RIS) network-assisted UAV millimeter-wave massive MIMO/FSO to improve system spectral efficiency. Firstly, the high-dimensional channel of RIS-assisted millimeter-wave massive MIMO/FSO in UAV is represented as a low-dimensional channel by tensor training decomposition. Secondly, the two-way gated recursive unit attention neural network model can effectively solve the FSO PE caused by UAV jitter, and the fast fading channel and Doppler frequency shift are estimated by the Fast Cyclic Tensor Power Method (FCTPM) based on tensor training decomposition. Finally, the RIS phase shift matrix is optimized by singular value decomposition. The hybrid beamforming and RIS phase-shift matrices were estimated by using the low-complexity phase extraction alternating minimization method to solve the beam misalignment problem. Simulation results show that by using the proposed method, the spectrum utilization rate is improved by 23.6% compared with other methods.
Article
Millimeter wave (mmWave) signals are sensitive to blockages in wireless channels. Traditional mmWave transceiver designs intend to harvest both beamsteering and spatial multiplexing gains, but without considering the potential change in the channel state incurred by sudden blockages. In this paper, we propose a blockage-resilient hybrid transceiver design for supporting robust data transmissions in the face of dynamic blockages. Upon exploiting the spatial structure of mmWave channels, we formulate a weighted spectral efficiency maximization problem by utilizing the statistical information concerning the potential future blockages of different path clusters, which uniquely distinguishes this work from existing transceiver optimization problems. On the basis of alternating optimization, we propose a two-stage algorithm to deal with the resultant non-convex problem riddled with highly coupled variables. First, we alternatively optimize the fully digital transmit precoder and receive equalizer by transforming the optimization problem into a quadratic form. Based on the Block Successive Upper-bound Minimization (BSUM) framework, the optimal fully digital precoder and equalizer can be found by exploiting the Karush-Kuhn-Tucker (KKT) conditions and the matrix monotonic method. Then, inspired by the sparse signal recovery philosophy, the hybrid analog/digital transceiver structure is designed for approximating the fully digital solution. Our numerical results show that the proposed design strikes an improved throughput vs. blockage-resilience trade-off compared to existing schemes, which demonstrates its superiority.
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We have recently seen a surge in interest in leveraging reconfigurable intelligent surfaces in smart radio environments. One critical question is how to efficiently optimize the phase configuration that results in the desired reflective wavefront. In this paper, we proposed a physics-based optimization approach inspired by the statistical mechanics of correlated spins and adiabatic quantum computing. The new concept is based on the isomorphism of electromagnetic scattered power and the Ising Hamiltonian. As a result, the problem of optimizing phase configuration is transformed into the problem of finding the ground state of the target Ising Hamiltonian. We successfully demonstrate the feasibility of combinatorial optimization for weighted beamforming and diffusive scattering applications using this framework.
Article
In this paper, to stabilize the users’ quality of service (QoS), the symbol detection mean squared error (MSE) constrained hybrid analog and digital beamforming is proposed in millimeter wave (mmWave) system, and the reconfigurable intelligent surface (RIS) is proposed to assist the mmWave system. The inner majorization-minimization (iMM) method is proposed to obtain analog transmitter, RIS and analog receivers, and the alternating direction method of multipliers (ADMM) method is proposed to obtain digital transmitter. The proposed iMM and ADMM methods are faster than the semidefinite relaxation (SDR) and interior point methods, respectively. In order to counter against the changing large-scale path loss, the iMM method is helped by channel normalization to reduce the computational complexity, while the ADMM method is helped by the adaptive parameterizations to robust against the changing large-scale path loss. Simulation results show that the computational times of the proposed method are much faster than other methods, the proposed method is robust against the changing large-scale path loss, and the user’s bit error rate (BER) is stable under small to medium channel estimation errors.
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In this paper, we propose a reconfigurable intelligent surface (RIS) assisted secure finite blocklength transmission framework in machine-type communications (MTC) networks, where the integration of millimeter-wave (mmWave) communication and non-orthogonal multiple access (NOMA) technology is considered to alleviate the problem of insufficient spectrum resources caused by massive MTC devices (MTCDs). For improving the ability of anti-eavesdropping, we aim to maximize the achievable sum secrecy capacity (SC) by jointly optimize the MTCDs’ transmission power, RIS phase coefficient and receive beamforming design. To handle the nonconvexity of the proposed optimization problem, we decouple it into three sub-problems, where the first two are solved by successive convex approximation (SCA) method. A minimum mean squared error successive interference cancellation (MMSE-SIC) scheme is proposed to tackle the receive beamforming problem for uplink NOMA networks. Furthermore, an alternating optimization based joint power, phase, and beamforming allocation (AO-JPPBA) algorithm is developed to implement joint optimization. Simulation results show that: 1) the security performance of the proposed AO-JPPBA is improved by 612.26% than the baseline scheme; 2) the proposed MMSE-SIC beamforming scheme is more effective in improving sum-SC of uplink NOMA networks; 3) RIS’s location has an obvious impact on sum-SC when considering eavesdroppers with strong wiretapping ability.
Article
Intelligent reflecting surface (IRS) has recently been envisioned to enhance the power of the desired received signal or suppress the interference signal by deploying low-cost passive reflection elements. This paper investigates an IRS-aided multi-cell millimeter wave (mmWave) communication system for suppressing inter-cell interference (ICI) to assist the downlink transmission of cell-edge users. We aim for maximizing the minimum weighted signal-to-interference-plus-noise ratio (SINR) through jointly optimizing the active beamforming vectors of mmWave base stations (MBSs), the phase shifts of the IRS, and the location of the IRS. Especially since it is challenging to obtain the perfect channel state information (CSI) related to the IRS links, we also study the performance of IRS-aided mmWave communication in the case of imperfect CSI. First, in the case of perfect CSI, to tackle the challenging and non-convex minimum weighted SINR maximization problem, we develop an alternating optimization (AO)-based beamforming algorithm via updating the active beamforming vectors at MBSs, the phase shifts at the IRS, and the location of the IRS alternately. Then, in the case of imperfect CSI, we propose a low-complexity majorization-minimization (MM)-based robust beamforming algorithm to obtain the benchmark performance. Moreover, the proposed algorithms are also extended to multi-IRS-aided multi-cell mmWave scenarios. Finally, the simulation results demonstrate the advantages in terms of the SINR, effective sum rate as well as energy efficiency after introducing the IRS to mitigate the ICI.
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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 propagation characteristics of mmWave signals. We propose a viable solution to implement the outdoor-to-indoor mmWave communication 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 indoor users (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 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 active-ITSs, 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 the 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 space-limited and aesthetic-needed scenario, and the performance degradation caused by the block-amplifying architecture is negligible.
Article
Providing satisfactory quality of service (QoS) in high-speed railway (HSR) network is being strangled by external interference as well as jamming. To address this issue, we study the reconfigurable intelligent surface (RIS)-aided HSR network, where one RIS is deployed nearby the onboard mobile relay (MR) to suppress the interference as well as jamming in HSR system. Aiming at enhancing the HSR network capacity against the interference, we formulate an optimization problem for designing the phase shifts at the RIS. Since the HSR environment is time-varying and complicated, the optimization problem is challenging to settle. Inspired by the recent advances of deep reinforcement learning (DRL), we propose a deep deterministic policy gradient (DDPG)-based scheme to settle the problem through designing the action space, the state space as well as the reward function. Simulation results present that 1) deploying the RIS nearby the onboard MR is strongly facilitative of suppressing the interference; 2) the proposed DDPG scheme can achieve better capacity than the baseline schemes, and be gradually close to the upper boundary with the number of RIS elements increasing.
Article
In this paper, energy efficiency (EE) is maximized for the reconfigurable intelligent surface (RIS) aided millimeter-Wave (mmWave) networks with non-orthogonal multiple access (NOMA) and multiple mobile devices. To this end, we first propose the EE optimization, under the constraints of maximum power, minimal rate of devices and constant modulus of beamforming (BF) vectors. Then, the joint resource allocation scheme of power allocation (PA) and BF is designed. Specifically, given PA, an effective iterative algorithm based on the majorizationminimization, concave-convex procedure and block coordinate descent (BCD) is presented to obtain closed-form solutions of suboptimal passive BF (PBF) and analog BF (ABF) for each iteration. Then, given PBF and ABF, an effective iterative algorithm based on the successive convex approximation, BCD and Dinkelbach methods is derived to achieve suboptimal closedform PA for each iteration. By incorporating these two algorithms into the BCD method, a joint optimization algorithm for EE maximization is presented. As a result, joint resource allocation of PA, PBF and ABF is attained. Besides, the convergence and complexity of the algorithms are analyzed. For comparison, the benchmark scheme based on the multidimensional search method and artificial bee colony algorithm is also presented. Simulation results show that the proposed joint scheme is effective and higher EE can be obtained with lower complexity.
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Reconfigurable intelligent surface (RIS) assisted millimeter wave (mmWave) communications has been envisioned as a prominent technology for future wireless networks, since it is capable of simultaneously providing abundant spectrum resources and favorable propagation environments. The small wavelength at mmWave bands also enables the widespread use of large antenna arrays, of which the hybrid beamforming structure has emerged as a cost-effective solution. In this paper, we aim to minimize the sum-mean-square-error (sum-MSE) in the RIS-assisted mmWave multiuser multiple input multiple output (MU-MIMO) system by jointly optimizing the hybrid analog-digital precoders and the RIS reflection matrix. We demonstrate that the role of RIS in assisting mmWave communications can be completely replaced by a large-scale Kronecker-structured hybrid array. Moreover, an accelerated Riemannian gradient algorithm using majorization minimization technique is proposed to tackle the unit-modulus constrained analog precoder/RIS design. Under the assumption of perfect channel state information (CSI), we firstly consider the single-user MIMO (SU-MIMO) setup and propose an effective alternating minimization (AM) procedure to characterize the system performance limit. Moreover, a two-stage scheme is developed for low-complexity implementation. This AM procedure is then extended to the general MU-MIMO scenario. In addition, we develop a novel enhanced regularized zero-forcing (ERZF) scheme for simultaneously combating strong noise in the low-SNR regime and mitigating multi-user interference (MUI) in the high-SNR regime. The optimality of our proposed algorithms is validated for some simplified practical scenarios. Numerical results illustrate that the proposed algorithms outperform existing benchmark schemes in terms of the actual complexity and performance.
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This article investigates physical layer security (PLS) in reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) channels. Existing researches ignore the problem that secrecy rate can not be calculated if the eavesdropper’s instantaneous channel state information (CSI) is unknown. Furthermore, without the secrecy rate expression, beamforming and phase shifter optimization with the purpose of PLS enhancement is not available. To address these problems, we first give the expression of secrecy outage probability for any beamforming vector and phase shifter matrix as the RIS-assisted PLS metric, which is measured based on the eavesdropper’s statistical CSI. Then, with the aid of the expression, we formulate the minimization problem of secrecy outage probability that is solved via alternately optimizing beamforming vectors and phase shift matrices. In the case of single-antenna transmitter or single-antenna legitimate receiver, the proposed alternating optimization (AO) scheme can be simplified to reduce computational complexity. Finally, it is demonstrated that the secrecy outage probability is significantly reduced with the proposed methods compared to current RIS-assisted PLS systems.
Article
Utilizing the millimeter-wave (mmWave) frequency is a promising solution to meet fast-growing traffic demand over wireless networks. However, mmWave communications are sensitive to physical obstructions on signal propagation. In this paper, the reconfigurable intelligent surfaces (RISs) are investigated to overcome the limitations of mmWave communications. Particularly, an RIS is deployed to reflect the mmWave signals towards vehicular users who experience direct link blockages that may occur due to static or dynamic obstacles. To this end, a risk-averse optimization problem is designed to optimize the Base Station (BS) precoding matrix and the RIS phase shifts under stochastic link blockages. A solution approach is developed in two phases: the BS precoding optimization and the RIS phase shift control phases. In the first phase, a Decomposition and Relaxation-based Precoding Optimization (DRPO) algorithm is developed to obtain the optimal precoding matrix. In the second phase, a learning-based method is introduced to dynamically adjust the direction of reflected signals under channel uncertainty. Extensive simulations are presented to validate the efficacy of the developed algorithms. The obtained results show that the developed algorithms can ensure reliable transmissions to users in non-LoS areas and improve network performance.
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