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.

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.

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.

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.

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 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.

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.

下行RIS-NOMA的用户集群方法

为提高用户分布非均匀的场景下可重构智能表面(RIS)辅助下行非正交多址(NOMA)通信系统的性能,提出了一种分布式RIS辅助下行NOMA的用户聚类方案。首先,采用自适应几何分布(AGD)聚类算法划分用户集群(UCs),从而为各UC匹配RIS。然后,利用分式规划(FP)方法将非凸最大化频谱效率问题转换为凸优化问题。最后,为UC内用户逐级进行功率分配(PA)与被动波束形成(PB)。仿真结果表明,与谱聚类(SPC)、K均值(K-means)、高斯混合模型(GMM)聚类方案和正交多址(OMA)方案相比,在AGD方案下,功率对频谱效率提升了7%、14%、19%和42%的增益,反射面对频谱效率提升了16%、19%、26%和40%的增益。

基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究

针对无人机(UAV)面对复杂时变的衰落信道对无线传输造成不利影响这一问题,构建了可重构智能表面(RIS)辅助UAV边缘计算网络中UAV轨迹、RIS相移、卸载时隙分配、CPU频率分配和用户设备(UE)传输功率的联合优化问题。为了求解构建的问题,对UE和UAV的任务队列稳定性约束进行转化,将多时隙随机性优化问题转化为每个时隙的确定性优化问题,提出了基于李雅普诺夫优化和块坐标下降(BCD)法的任务卸载与资源分配(JORL)方法。首先基于三角不等式求解RIS相移并求得闭合表达式;然后使用非凸转凸问题的技术求解卸载时隙分配、CPU频率分配和UE传输功率;最后基于连续凸近似方法求解UAV轨迹。仿真结果表明,JORL在保证任务队列稳定性和降低能耗方面有较优越的性能。

联合RIS子块与接收天线的索引调制方案性能分析

利用大量无源反射器件设计的可重构智能表面(RIS),具有拓展无线通信覆盖范围、降低系统成本/功耗和提升未来通信系统性能的优势;而索引调制(IM),通过激活通信资源的子集可实现信息的隐性传输,有望为无线通信带来更高的频谱效率和能量效率,因此,为进一步提升未来无线通信系统的性能,该论文融合RIS与IM技术,提出一种联合RIS子块与接收天线的IM方案。在该方案中,按照相邻原则,将RIS反射元件分割为若干子块,进而利用RIS子块索引与接收天线索引同时实现附加信息传递,即对待传输比特序列,将其分割为三部分,其中第一部比特被调制为星座符号,第二部分用于指示RIS子块划分,第三部分用于指示接收天线索引;在此基础上,根据最大似然(ML)检测的成对错误概率(PEP)解析形式,分四种情况,从理论上推导出对应的矩母函数(MGF),得到无条件PEP的解析表达式,最后得到该方案ML检测的平均误码率(ABER)性能上界。仿真结果表明,与现有RIS辅助的IM方案相比,无须增加额外频谱资源,所提方案的系统可达速率和系统差错性能方面均具有一定优势;同时,验证了ML检测的ABER上界具备严格一致性。

多RIS辅助车载通信信号优化及部署规划

针对匀变速运动的汽车产生的多普勒扩展和时延扩展以及接收信噪比的问题,提出了一种多智能超表面(RIS)辅助匀变速移动物体通信的方案。与传统信道估计不同的是,使用了信道增益的方法和优化RIS相位以及多目标优化来让移动物体能达到最大接收瞬时信噪比的同时,获得小的多普勒扩展和时延扩展。通过优化后的RIS相位来研究RIS的位置对接收信号的影响,分别研究了RIS之间的距离以及RIS之间距离一定时,RIS摆放在什么位置使得接收信号的信噪比以及时延扩展保持较低的范围,对于这个问题提出了相对运动的理论,且各自提出一种算法解决这两个问题。仿真表明,多RIS辅助的通信系统对车载通信接收信号的功率提升了约10 dB。RIS的部署位置应该让第一个RIS靠近基站并且RIS之间的距离在现实允许的情况下尽可能靠近。由此多RIS的通信方案可以广泛应用于车载通信中。

STAR-RIS辅助的NOMA系统物理层安全性能优化

针对实际通信场景中非理想信道状态信息以及非理想串行干扰删除等非理想因素的强耦合特性使可同时反射和透射的可重构智能超表面(STAR-RIS)辅助的非正交多址接入(NOMA)传输系统安全性能无法准确衡量的问题,提出了基于惩罚对偶分解(PDD)和块坐标下降(BCD)的融合算法,联合优化基站的波束成形矢量和STAR-RIS相移系数,实现系统最低安全传输速率的最大化。结果表明,所提融合算法相比BCD算法可以明显增加最低安全传输速率,性能至少提升10%。

一种基于GABP神经网络的RIS辅助近场无线定位方法

可重构智能表面(RIS)是6G潜在关键技术,将其部署在无线通信系统中,可辅助基站对用户进行定位,并提高定位性能。在毫米波频段,由于频率较高,RIS面板的阵列孔径及反射单元个数较大,近场区域范围扩大,用户将大概率处于RIS的近场区域中。为此,考虑RIS辅助的无线通信系统在近场条件下对用户进行定位,将用户定位问题建模为参数估计问题,并利用最大似然估计来实现对用户三维坐标参数的估计。为求解所建立的最大似然估计问题,结合遗传算法与反向传播算法神经网络的优势,提出了一种计算效率更高的GABP算法。仿真结果表明,所提GABP算法比传统的遗传算法计算效率更高。

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.

基于列车先验信息的RIS-MIMO系统鲁棒波束成形算法

针对高移动性场景中完美信道状态信息(CSI)难以获取导致的智能超表面多输入多输出(RIS-MIMO)系统主被动波束成形算法性能恶化的问题,构建了RIS辅助的高铁毫米波MIMO中继通信模型。首先,在列车位置信息不完全的情况下,估计并推导了RIS-车载移动中继(MRN)之间视线战略(LOS)路径角度估计误差的统计特性;其次,对毫米波MIMO系统的中断性能进行了研究,给出了以信道容量作为中断判决的中断概率表达式;最后,将优化问题建模为5G基站(gNB)发射功率约束的中断概率最小化问题,提出了一种基于黎曼共轭梯度下降的复圆流形优化算法并求解该问题。仿真结果表明,与现有算法和传统的无RIS系统以及RIS随机相位调节下的高铁通信系统相比,所提算法具有更快的收敛速度和更高的系统鲁棒性。

基于RIS的二维波达角估计系统设计与实现

新兴的智能超表面(Reconfigurable Intelligent Surface,RIS)技术作为6G潜在关键使能技术之一,通过大量的电磁单元智能调控无线信号的反射特性,有望实现对无线传播环境的主动增强与感知,其在角度感知估计方面的应用受到广泛关注。现有文献报道的RIS波达角估计硬件实现工作中,RIS往往采用固定列控或行控的编码方式,无法充分发挥其空间维度自由度,只能进行一维的波达角估计。在此背景下,本论文设计了一套灵活的智能超表面控制平台,实现对每个电磁单元的独立且高速的控制,充分发挥RIS硬件的空间自由度,并在此平台上实现基于RIS的二维波达角实时估计功能。首先,介绍基于RIS的波达角估计系统设计方案,通过对RIS进行高速空时编码调制,使反射信号的谐波分量与入射信号的波达角建立映射关系,在接收端利用反射信号各谐波的幅度和相位信息,对入射信号波达角进行实时估计。随后,基于所提方案设计系统的无线帧结构相关参数,构建基于RIS的二维波达角实时估计原型系统。最后,使用原型系统开展测量实验,在多个测量点位对波达角的方位角和俯仰角分量进行估计与数据记录,实测数据验证了所提方案的可行性。

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.