Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

Rate optimization using low complex methods with reconfigurable intelligent surfaces

With the help of a developing technology called reconfigurable intelligent surfaces(RISs),it is possible to modify the propagation environment and boost the data rates of wireless communication networks.In this article,we optimized the phases of the RIS elements and performed a fair power allocation for each subcarrier over the full bandwidth in a single-input-single-output(SISO)wideband system where the user and the access point(AP)are provided with a single antenna.The data rate or its equivalent channel power is maximized by proposing different low-complex algorithms.The strongest tap maximization(STM)and power methods are compared with the semidefinite relaxation(SDR)method in terms of computational complexity and data rate performance.Runtime and complexity analysis of the suggested methods are computed and compared to reveal the actual time consumption and the required number of operations for each method.Simulation results show that with an optimized RIS,the sum rate is 2.5 times higher than with an unconfigured surface,demonstrating the RIS's tremendous advantages even in complex configurations.The data rate performance of the SDR method is higher than the power method and less than the STM method but with higher computational complexity,more than 6 million complex operations,and 50 min of runtime calculations compared with the other STM and power optimization methods.

Wireless communications empowered by reconfigurable intelligent surfaces: Model-based vs model-free channel estimation

Reconfigurable intelligent surfaces(RISs)are lately being attractive for their great potential in future sixth generation wireless communications(6G),which is attributed to their affordable energy consumption and easy integration.However,the large numbers of low-cost reflecting elements comprising RISs impose challenges for channel acquisition in various RIS-based wireless applications,such as RIS-enhanced orthogonal frequency-division multiplexing and multi-user multipleinput multiple-output systems.In this article,we first overview the state-of-the-art RIS hardware architectures designed to assist channel estimation for RIS-empowered wireless communication systems.We also overview existing channel estimation approaches,which are categorized into model-based and model-free techniques,and discuss their advantages and limitations depending on the RIS deployment.Design challenges with RIS-empowered systems in terms of hardware and other parameter limitations are presented,together with future research directions for channel estimation in RIS-based wireless systems,such as RISs with extremely large numbers of elements,multi-hop communications with RISs,and frequency division duplexing for high mobility systems.

Effects of realistic reradiation models in digital reconfigurable intelligent surfaces

Reconfigurable intelligent surfaces(RISs)are a promising technology for wireless communication applications,but their performance is often optimized using simplified electromagnetic reradiation models.In this study,we explore the impact on the RIS performance of more realistic assumptions,including the(possibly imperfect)quantization of the reflection coefficients,subwavelength inter-element spacing,near-field location,and presence of electromagnetic interference.We find that design constraints can cause an RIS to reradiate power in unwanted directions.Therefore,it is important to optimize an RIS by considering the entire reradiation pattern.Overall,our study indicates that a 2-bit digitally controllable RIS with a nearly constant reflection amplitude and RIS elements with a size and inter-element spacing between(1/8)th and(1/4)th of the signal wavelength may offer a reasonable tradeoff between performance,complexity,and cost.

Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

Reconfigurable intelligent surfaces for 6G:applications,challenges,and solutions

Scholars are expected to continue enhancing the depth and breadth of theoretical research on reconfigurable intelligent surface(RIS)to provide a higher theoretical limit for RIS engineering applications.Notably,significant advancements have been achieved through both academic research breakthroughs and the promotion of engineering applications and industrialization.We provide an overview of RIS engineering applications,focusing primarily on their typical features,classifications,and deployment scenarios.Furthermore,we systematically and comprehensively analyze the challenges faced by RIS and propose potential solutions including addressing the beamforming issues through cascade channel decoupling,tackling the effects and resolutions of regulatory constraints on RIS,exploring the network-controlled mode for RIS system architecture,examining integrated channel regulation and information modulation,and investigating the use of the true time delay(TTD)mechanism for RIS.In addition,two key technical points,RIS-assisted non-orthogonal multiple access(NOMA)and RIS-based transmitter,are reviewed from the perspective of completeness.Finally,we discuss future trends and challenges in this field.

Reconfigurable Intelligent Surfaces for 6G:Nine Fundamental Issues and One Critical Problem

Thanks to the recent advances in metamaterials,Reconfigurable Intelligent Surface(RIS)has emergedas a promising technology for future 6G wireless communications.Benefiting from its high array gain,low cost,and low power consumption,RISs are expected to greatly enlarge signal coverage,improve system capacity,andincrease energy efficiency.In this article,we systematically overview the emerging RIS technology with the focuson its key basics,nine fundamental issues,and one critical problem.Specifically,we first explain the RIS basics,including its working principles,hardware structures,and potential benefits for communications.Based on thesebasics,nine fundamental issues of RISs,such as“What’s the differences between RISs and massive MIMO?”and“Is RIS really intelligent?”,are explicitly addressed to elaborate its technical features,distinguish it from existingtechnologies,and clarify some misunderstandings in the literature.Then,one critical problem of RISs is revealedthat,due to the“multiplicative fading”effect,existing passive RISs can hardly achieve visible performance gains inmany communication scenarios with strong direct links.To address this critical problem,a potential solution calledactive RISs is introduced,and its effectiveness is demonstrated by numerical simulations.

Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Reconfigurable Intelligent Surfaces: Design, Implementation, and Practical Demonstration

Metasurfaces,ultrathin two-dimensional version of metamaterials,have attracted tremendous attention due to their exotic capabilities to freely manipulate electromagnetic waves.By incorporating various tunable materials or elements into metasurface designs,reconfigurable metasurfaces and related metadevices with functionalities controlled by external stimuli can be realized,opening a new avenue to achieving dynamic manipulation of electromagnetic waves.Recently,based on the tunable metasurface concept,reconfigurable intelligent surfaces(RISs)have received significant attention and have been regarded as a promising emerging technology for future wireless communication due to their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment.Here,in this article,we first focus on technical issues of RIS system implementation by reviewing the existing research contributions,paying special attention to designs in the microwave regime.Then,we showcase our recent attempts to practically demonstrate RIS systems in real-world applications,including deploying reflective RIS systems in indoor scenarios to enhance the wireless network coverage and utilizing intelligent omni-metasurfaces to improve both indoor and through-wall wireless communication quality.Finally,we give our own perspectives on possible future directions and existing challenges for RISs toward a truly commercial intelligent technology platform.

Field trial measurement and channel modeling for reconfigurable intelligent surface

With the advantage of programmable electromagnetic properties,Reconfigurable Intelligent Surfaces(RISs)havedrawn wide attention from both industry and academia.RIS-assisted communication systems can promote hugewireless channel quality improvement and remarkable coverage enhancement.This paper proposes generalpathloss model,radiation pattern and mirror beam effect of 1-bit RIS at sub-6 GHz band.Field trails have beencarried out in outdoor and indoor deployment scenarios.The proposed model is validated through extensivesimulations and field-trial measurements.In addition,an optimized RIS phase-shit design process for the mirrorbeam elimination is proposed and validated with simulations.The proposed theoretical model and measurementresults can promote future research and application in RIS-assisted communications.

Reconfigurable intelligent surfaces for wireless communications:Overview of hardware designs,channel models,and estimation techniques

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

Joint Optimization Scheme for the Reconfigurable Intelligent Surface-Assisted Untrusted Relay Networks

To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.

Reconfigurable Intelligent Surface-Based Hybrid Phase and Code Modulation for Symbiotic Radio

Reconfigurable intelligent surface(RIS)-assisted symbiotic radio is a spectrum-and energy-efficient communication paradigm,in which an RIS performs passive beamforming to enhance active transmission,while using the electromagnetic waves from the active transmission for additional information transfer(i.e.,passive transmission).In this paper,a hybrid RIS-based modulation,termed hybrid phase and code modulation(HPCM),is proposed to improve the reliability of RIS-assisted symbiotic radio.In RIS-HPCM,the RIS simultaneously performs direct sequence spread spectrum and passive beamforming on incident signals.Moreover,both the spreading code and phase offset are exploited to carry the RIS’s own information.A low-complexity detector is designed,in which the receiver first detects the spreading codes and then demodulates the constellation symbols.We analyze the bit error rate(BER)performance of RIS-HPCM over Rician fading channels.BER upper bounds and approximate BER expressions are derived in closed-form for maximum-likelihood and low-complexity detectors,respectively.Simulation results in terms of BER verify the analysis and show the superiority of RIS-HPCM over the existing RIS-based modulation.

Monte-Carlo based random passive energy beamforming for reconfigurable intelligent surface assisted wireless power transfer

Reconfigurable intelligent surface(RIS)employs passive beamforming to control the wireless propagation channel,which benefits the wireless communication capacity and the received energy efficiency of wireless power transfer(WPT)systems.Such beamforming schemes are classified as discrete and non-convex integer program-ming problems.In this paper,we propose a Monte-Carlo(MC)based random energy passive beamforming of RIS to achieve the maximum received power of electromagnetic(EM)WPT systems.Generally,the Gibbs sampling and re-sampling methods are employed to generate phase shift vector samples.And the sample with the maximum received power is considered the optimal solution.In order to adapt to the application scenarios,we develop two types of passive beamforming algorithms based on such MC sampling methods.The first passive beamforming uses an approximation of the integer programming as the initial sample,which is calculated based on the channel information.And the second one is a purely randomized algorithm with the only total received power feedback.The proposed methods present several advantages for RIS control,e.g.,fast convergence,easy implementation,robustness to the channel noise,and limited feedback requirement,and they are applicable even if the channel information is unknown.According to the simulation results,our proposed methods outperform other approxi-mation and genetic algorithms.With our methods,the WPT system even significantly improves the power effi-ciency in the nonline-of-sight(NLOS)environment.

Differential Scheme for Reconfigurable Intelligent Surface-Based Spatial Modulation System

In this paper,a differential scheme is proposed for reconfigurable intelligent surface(RIS)assisted spatial modulation,which is referred to as RISDSM,to eliminate the need for channel state information(CSI)at the receiver.The proposed scheme is an improvement over the current differential modulation scheme used in RIS-based systems,as it avoids the high-order matrix calculation and improves the spectral efficiency.A mathematical framework is developed to determine the theoretical average bit error probability(ABEP)of the system using RIS-DSM.The detection complexity of the proposed RIS-DSM scheme is extremely low through the simplification.Finally,simulations results demonstrate that the proposed RIS-DSM scheme can deliver satisfactory error performance even in low signal-to-noise ratio environments.

Joint Beamforming Optimization for Reconfigurable Intelligent Surface-Enabled MISO-OFDM Systems

In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.

Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication Systems in Mobility Scenarios

Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.

Enhanced Reconfigurable Intelligent Surface Assisted mmWave Communication: A Federated Learning

Reconfigurable intelligent surface(RIS)has been proposed as a potential solution to improve the coverage and spectrum efficiency for future wireless communication.However,the privacy of users’data is often ignored in previous works,such as the user’s location information during channel estimation.In this paper,we propose a privacy-preserving design paradigm combining federated learning(FL)with RIS in the mmWave communication system.Based on FL,the local models are trained and encrypted using the private data managed on each local device.Following this,a global model is generated by aggregating them at the central server.The optimal model is trained for establishing the mapping function between channel state information(CSI)and RIS’configuration matrix in order to maximize the achievable rate of the received signal.Simulation results demonstrate that the proposed scheme can effectively approach to the theoretical value generated by centralized machine learning(ML),while protecting user’privacy.

Secrecy Rate Analysis for Reconfigurable Intelligent Surface-Assisted MIMO Communications with Statistical CSI

In this paper,a reconfigurable intelligent surface(RIS)-assisted MIMO wireless secure communication system is considered,in which a base station(BS)equipped with multiple antennas exploits statistical channel state information to communicate with a legitimate multi-antenna user,in the presence of an eavesdropper,also equipped with multiple antennas.We firstly obtain an analytical expression of the ergodic secrecy rate based on the results of largedimensional random matrix theory.Then,a jointly alternating optimization algorithm with the method of Taylor series expansion and the projected gradient ascent method is proposed to design the transmit covariance matrix at the BS,as well as the diagonal phaseshifting matrix to maximize the ergodic secrecy rate.Simulations are conducted to demonstrate the accuracy of the derived analytical expressions,as well as the superior performance of our proposed algorithm.

AIRIS:Artificial Intelligence Enhanced Signal Processing in Reconfigurable Intelligent Surface Communications

Reconfigurable intelligent surface(RIS)is an emerging meta-surface that can provide additional communications links through reflecting the signals,and has been recognized as a strong candidate of 6G mobile communications systems.Meanwhile,it has been recently admitted that implementing artificial intelligence(AI)into RIS communications will extensively benefit the reconfiguration capacity and enhance the robustness to complicated transmission environments.Besides the conventional model-driven approaches,AI can also deal with the existing signal processing problems in a data-driven manner via digging the inherent characteristic from the real data.Hence,AI is particularly suitable for the signal processing problems over RIS networks under unideal scenarios like modeling mismatching,insufficient resource,hardware impairment,as well as dynamical transmissions.As one of the earliest survey papers,we will introduce the merging of AI and RIS,called AIRIS,over various signal processing topics,including environmental sensing,channel acquisition,beamforming design,and resource scheduling,etc.We will also discuss the challenges of AIRIS and present some interesting future directions.