Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although...Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.展开更多
Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO sate...Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.展开更多
Inspired by mobile edge computing(MEC),edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data center.However,the quality of model t...Inspired by mobile edge computing(MEC),edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data center.However,the quality of model training will be affected by the limited communication and computing resources of network edge.In this paper,how to improve the training performance of a federated learning system aided by intelligent reflecting surface(IRS)over vehicle platooning networks is studied,where multiple platoons train a shared federated learning model.Multi-platoon cooperation can alleviate the pressure of data processing caused by the limited computing resources of single platoon.Meanwhile,IRS can enhance the inter-platoon communication in a cost-effective and energy-efficient manner.Firstly,the federated learning optimization problem of maximizing the learning accuracy is formulated by jointing platoon scheduling,bandwidth allocation and phase shifts at the IRS to maximize the number of scheduled platoon.Specif-ically,in the proposed learning architecture each platoon updates the learning model with its own data and uploads it to the global model through IRS-based wireless networks.Then,a method based on sequential optimization algorithm(SOA)and a group-based optimization method are analyzed for single IRS aided and large-scale IRS aided commu-nication,respectively.Finally,a platoon scheduling scheme is designed based on the communication reliability and computing reliability of platoons.Simulation results demonstrate that large-scale IRS assisted communication can effectively improve the reliability of multi-user communication networks.The scheduling scheme based on learning reliability balances the communication performance and computing performance of platoons.展开更多
Active intelligent reflecting surface(IRS)is a novel and promising technology that is able to overcome the multiplicative fading introduced by passive IRS.In this paper,we consider the application of active IRS to non...Active intelligent reflecting surface(IRS)is a novel and promising technology that is able to overcome the multiplicative fading introduced by passive IRS.In this paper,we consider the application of active IRS to nonorthogonalmultiple access(NOMA)networks,where the incident signals are amplified actively through integrating amplifier to reflecting elements.More specifically,the performance of active/passive IRS-NOMA networks is investigated over large and small-scale fading channels.Aiming to characterize the performance of active IRSNOMA networks,the exact and asymptotic expressions of outage probability for a couple of users,i.e.,near-end user n and far-end user m are derived by exploiting a 1-bit coding scheme.Based on approximated analyses,the diversity orders of user n and user m are obtained for active IRS-NOMA.In addition,the system throughput of active IRS-NOMA is discussed in the delay-sensitive transmission.The simulation results are carried out to verify that:i)The outage behaviors of active IRS-NOMAnetworks are superior to that of passive IRS-NOMAnetworks;ii)As the reflection amplitude factors increase,the active IRS-NOMAnetworks are capable of furnishing the enhanced outage performance;and iii)The active IRS-NOMA has a larger system throughput than passive IRS-NOMA and conventional communications.展开更多
In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)con...In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.展开更多
Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a c...Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.展开更多
Terahertz(THz)communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation(6G)wireless networks.In order to mitigate blockage v...Terahertz(THz)communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation(6G)wireless networks.In order to mitigate blockage vulnerability caused by serious propagation attenuation and poor diffraction of THz waves,an intelligent reflecting surface(IRS),which manipulates the propagation of incident electromagnetic waves in a programmable manner by adjusting the phase shifts of passive reflecting elements,is proposed to create smart radio environments,improve spectrum efficiency and enhance coverage capability.Firstly,some prospective application scenarios driven by the IRS empowered THz communications are introduced,including wireless mobile communications,secure communications,unmanned aerial vehicle(UAV)scenario,mobile edge computing(MEC)scenario and THz localization scenario.Then,we discuss the enabling technologies employed by the IRS empowered THz system,involving hardware design,channel estimation,capacity optimization,beam control,resource allocation and robustness design.Moreover,the arising challenges and open problems encountered in the future IRS empowered THz communications are also highlighted.Concretely,these emerging problems possibly originate from channel modeling,new material exploration,experimental IRS testbeds and intensive deployment.Ultimately,the combination of THz communications and IRS is capable of accelerating the development of 6G wireless networks.展开更多
In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by s...In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.展开更多
A joint beamforming algorithm is proposed for intelligent reflecting surface(IRS) aided wireless multiple-input multiple-output(MIMO) communication using statistical channel state information(CSI). The beamforming is ...A joint beamforming algorithm is proposed for intelligent reflecting surface(IRS) aided wireless multiple-input multiple-output(MIMO) communication using statistical channel state information(CSI). The beamforming is done by alternatively optimizing the IRS reflecting coefficients and the covariance matrix of the transmit symbol vector, such that the ergodic rate of the system is maximized. The algorithm utilizes only the second order momentum of the random channel matrices and does assume any specific channel distribution, leading to a general framework for ergodic rate evaluation. A practical channel correlation model is configured to validate the performance gain. It is found that the rate can be enlarged by the joint optimization algorithm, however, the gain over that of randomly deployed reflecting coefficients depends highly on the relative correlation distance of the IRS elements and the spatial position of the IRS. In particular, the results suggest that IRS should be placed in the vicinity of either the transmitter or the receiver. Placing IRS far away from those positions is non-beneficial.展开更多
This paper considers a secure multigroup multicast multiple-input single-output(MISO)communication system aided by an intelligent reflecting surface(IRS).Specifically,we aim to minimize the transmit power at Alice via...This paper considers a secure multigroup multicast multiple-input single-output(MISO)communication system aided by an intelligent reflecting surface(IRS).Specifically,we aim to minimize the transmit power at Alice via jointly optimizing the transmit beamformer,artificial noise(AN)vector and phase shifts at the IRS subject to the secrecy rate constraints as well as the unit modulus constraints of IRS phase shifts.To tackle the optimization problem,we first transform it into a semidefinite relaxation(SDR)problem,and then alternately update the transmit beamformer and AN matrix as well as the phase shifts at the IRS.In order to reduce the high computational complexity,we further propose a low-complexity algorithm based on second-order cone programming(SOCP).We decouple the optimization problem into two sub-problems and optimize the transmit beamformer,AN vector and the phase shifts alternately by solving two corresponding SOCP subproblem.Simulation results show that the proposed SDR and SOCP schemes require half or less transmit power than the scheme without IRS,which demonstrates the advantages of introducing IRS and the effectiveness of the proposed methods.展开更多
Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread attention.However, the process o...Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread attention.However, the process of FL involves frequent communications between the server and mobile devices,which incurs a long latency. Intelligent reflecting surface(IRS) provides a promising technology to address this issue, thanks to its capacity to reconfigure the wireless propagation environment. In this paper, we exploit the advantage of IRS to reduce the latency of FL. Specifically, we formulate a latency minimization problem for the IRS assisted FL system, by optimizing the communication resource allocations including the devices’ transmit-powers, the uploading time, the downloading time, the multi-user decomposition matrix and the phase shift matrix of IRS. To solve this non-convex problem, we propose an efficient algorithm which is based on the Block Coordinate Descent(BCD) and the penalty difference of convex(DC) algorithm to compute the solution. Numerical results are provided to validate the efficiency of our proposed algorithm and demonstrate the benefit of deploying IRS for reducing the latency of FL. In particular, the results show that our algorithm can outperform the baseline of Majorization-Minimization(MM) algorithm with the fixed transmit-power by up to 30%.展开更多
Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive ...Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.展开更多
The performance of symbiotic radio(SR)networks can be improved by equipping secondary transmitters(STs)with intelligent reflecting surfaces(IRSs).Since the IRS power consumption is a non-negligible issue for STs,we co...The performance of symbiotic radio(SR)networks can be improved by equipping secondary transmitters(STs)with intelligent reflecting surfaces(IRSs).Since the IRS power consumption is a non-negligible issue for STs,we consider an IRS assisted SR system where the IRS operates under power splitting(PS)mode.We aim at minimizing the IRS power consumption for the ST under the quality of service constraints for both primary and secondary transmissions by optimizing the transmit beamforming,the reflect beamforming and the PS factor.The optimization problem is non-convex.To tackle it,an algorithm is proposed by employing the block coordinate descent,semidefinite relaxation and alternating direction method of multipliers techniques.Simulation results demonstrate the efficiency and effectiveness of the proposed algorithm.展开更多
The new requirements from the 5<sup>th</sup> and the 6<sup>th</sup> generation of wireless communication are ultra-high data rate, energy efficiency, wide coverage and connectivity, high reliab...The new requirements from the 5<sup>th</sup> and the 6<sup>th</sup> generation of wireless communication are ultra-high data rate, energy efficiency, wide coverage and connectivity, high reliability, and low latency. The current technologies cannot achieve all the mentioned requirements. New technologies and new approaches for deploying more active and passive nodes must be developed. Furthermore, the use of MMW band and THz band (30 - 300 GHz), in order to utilize their huge bandwidth, results in deploying more active node and more antennas due to high propagation losses and “LOS” behavior at this band. Development of innovative technologies is necessary to realize the above demand for growth of future wireless communication. The main task is to suggest solutions for the time varying characteristic of the wireless channel due to the user mobility and shadowing or blocking of communication channel. The current methods such as use of pilot channel to estimate the fading, various modulation or coding and beamforming, have overhead and limitations over random (large, unexpected changes) channels.展开更多
In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(I...In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(IRS),we propose a deep learning-based channel estimation scheme.The proposed scheme employs a hybrid active/passive IRS architecture,wherein the least square(LS)algorithm is initially utilized to acquire the channel estimate from the active elements.Subsequently,this estimation is interpolated to obtain a preliminary channel estimation and ultimately refined into an accurate estimate of the channel using the channel super-resolution convolutional neural network(Chan-SRCNN)deep learning network.The simulation results demonstrate that the proposed scheme surpasses LS,orthogonal matching pursuit(OMP),synchronous OMP(SOMP),and deep neural network(DNN)channel estimation algorithms in terms of normalized mean squared error(NMSE)performance,thereby validating the feasibility of the proposed approach.展开更多
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 b...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.展开更多
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)-e...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.展开更多
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 reco...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.展开更多
This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communication.With the popularization of UAV technology,more and more communication ...This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communication.With the popularization of UAV technology,more and more communication scenarios need UAV support.We consider using IRS to improve the secrecy efficiency.Specifically,IRS and UAV trajectories work together to counter potential eavesdroppers,while balancing the secrecy rate and energy consumption.The original problem is difficult to solve due to the coupling of optimization variables.We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem,and then prove the equivalence between relaxation problem and the original problem.Then an iterative algorithm is proposed by applying the block coordinate descent(BCD)method and the inner approximationmethod.The simulation results show that the proposed algorithm converges fast and is superior to the existing schemes.In addition,in order to improve the robustness of the algorithm,we also pay attention to the case of obtaining imperfect channel state information(CSI).展开更多
Intelligent reflecting surface(IRS)is a revolutionizing and promising technology to improve the high transmission rate of the wireless communication systems.Specifically,an IRS consists of a great amount of low-cost p...Intelligent reflecting surface(IRS)is a revolutionizing and promising technology to improve the high transmission rate of the wireless communication systems.Specifically,an IRS consists of a great amount of low-cost passive reflecting elements,which reflect the incident signals to the desired user by collaboratively using passive beamforming.This paper introduces IRSs into a device-to-device(D2D)underlying cellular system to enhance transmission rate performance of the D2D pairs.We formulate an optimization problem of maximizing the transmission rate of the D2D pairs while satisfying the minimum required rate of the cellular users.We address this problem by jointly optimizing the reuse indicator,received beamforming,power allocation,and phase shift matrices.Block coordinate descent(BCD)algorithm is adopted to decouple the original problem into four subproblems.Closed form solutions are obtained by solving the sub-problems of optimizing the received beamforming and power allocation.Then,Kuhn-Munkres(KM)algorithm and minimization-majorization(MM)algorithm are adopted to solve the sub-problems of optimizing the reuse indicator and phase shift matrices,respectively.Simulation results demonstrate that IRSs can effectively improve the transmission rate of the D2D pairs and our proposed distributed IRSs scheme outperforms the other benchmark schemes.展开更多
基金supported by the National Natural Science Foundation of China 62001051.
文摘Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.
基金supported by the National Key R&D Program of China under Grant 2020YFB1807900the National Natural Science Foundation of China (NSFC) under Grant 61931005Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.
基金supported in part by National Key Research and Development Project under Grant 2020YFB1807204in part by the National Natural Science Foundation of China under Grant U2001213,61971191+2 种基金in part by the Beijing Natural Science Foundation under Grant L201011in part by the Key project of Natural Science Foundation of Jiangxi Province under Grant 20202ACBL202006in part by the Science and Technology Foundation of Jiangxi Province(20202BCD42010).
文摘Inspired by mobile edge computing(MEC),edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data center.However,the quality of model training will be affected by the limited communication and computing resources of network edge.In this paper,how to improve the training performance of a federated learning system aided by intelligent reflecting surface(IRS)over vehicle platooning networks is studied,where multiple platoons train a shared federated learning model.Multi-platoon cooperation can alleviate the pressure of data processing caused by the limited computing resources of single platoon.Meanwhile,IRS can enhance the inter-platoon communication in a cost-effective and energy-efficient manner.Firstly,the federated learning optimization problem of maximizing the learning accuracy is formulated by jointing platoon scheduling,bandwidth allocation and phase shifts at the IRS to maximize the number of scheduled platoon.Specif-ically,in the proposed learning architecture each platoon updates the learning model with its own data and uploads it to the global model through IRS-based wireless networks.Then,a method based on sequential optimization algorithm(SOA)and a group-based optimization method are analyzed for single IRS aided and large-scale IRS aided commu-nication,respectively.Finally,a platoon scheduling scheme is designed based on the communication reliability and computing reliability of platoons.Simulation results demonstrate that large-scale IRS assisted communication can effectively improve the reliability of multi-user communication networks.The scheduling scheme based on learning reliability balances the communication performance and computing performance of platoons.
基金supported by the National Natural Science Foundation of China Grant 61901043.
文摘Active intelligent reflecting surface(IRS)is a novel and promising technology that is able to overcome the multiplicative fading introduced by passive IRS.In this paper,we consider the application of active IRS to nonorthogonalmultiple access(NOMA)networks,where the incident signals are amplified actively through integrating amplifier to reflecting elements.More specifically,the performance of active/passive IRS-NOMA networks is investigated over large and small-scale fading channels.Aiming to characterize the performance of active IRSNOMA networks,the exact and asymptotic expressions of outage probability for a couple of users,i.e.,near-end user n and far-end user m are derived by exploiting a 1-bit coding scheme.Based on approximated analyses,the diversity orders of user n and user m are obtained for active IRS-NOMA.In addition,the system throughput of active IRS-NOMA is discussed in the delay-sensitive transmission.The simulation results are carried out to verify that:i)The outage behaviors of active IRS-NOMAnetworks are superior to that of passive IRS-NOMAnetworks;ii)As the reflection amplitude factors increase,the active IRS-NOMAnetworks are capable of furnishing the enhanced outage performance;and iii)The active IRS-NOMA has a larger system throughput than passive IRS-NOMA and conventional communications.
基金supported in part by the Joint Research Fund for Guangzhou University and Hong Kong University of Science and Technology under Grant No.YH202203the Guangzhou Basic Research Program Municipal School(College)Joint Funding Project,the Research Project of Guizhou University for Talent Introduction under Grant No.[2020]61+7 种基金the Cultivation Project of Guizhou University under Grant No.[2019]56the Open Fund of Key Laboratory of Advanced Manufacturing Technology,Ministry of Education under Grant No.GZUAMT2021KF[01]the National Natural Science Foundation of China under Grant Nos.51978089 and 62171119the Key R&D Plan of Sichuan Science and Technology Department under Grant No.22ZDYF2726the Chengdu Normal University Scientific Research and Innovation Team under Grant Nos.CSCXTD2020B09,ZZBS201907,CS21ZC01the Open Project of Intelligent Manufacturing Industry Technology Research Institute under Grant No.ZNZZ2208the National Key Research and Development Program of China under Grant No.2020YFB1807201Key research and development plan of Jiangsu Province under Grant No.BE2021013-3.
文摘In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.
基金supported in part by National Natural Science Foundation of China under Grant 62071202in part by Shandong Provincial Natural Science Foundation under Grants ZR2020MF009,ZR2020MF075in part by Shandong Key Laboratory of Intelligent Buildings Technology undert Grant SDIBT202004.
文摘Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.
基金supported by the National Key Research and Development Project of China under Grant 2018YFB1801500supported in part by The National Natural Science Foundation of China under Grant 6162780166 and Grant 61831012.
文摘Terahertz(THz)communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation(6G)wireless networks.In order to mitigate blockage vulnerability caused by serious propagation attenuation and poor diffraction of THz waves,an intelligent reflecting surface(IRS),which manipulates the propagation of incident electromagnetic waves in a programmable manner by adjusting the phase shifts of passive reflecting elements,is proposed to create smart radio environments,improve spectrum efficiency and enhance coverage capability.Firstly,some prospective application scenarios driven by the IRS empowered THz communications are introduced,including wireless mobile communications,secure communications,unmanned aerial vehicle(UAV)scenario,mobile edge computing(MEC)scenario and THz localization scenario.Then,we discuss the enabling technologies employed by the IRS empowered THz system,involving hardware design,channel estimation,capacity optimization,beam control,resource allocation and robustness design.Moreover,the arising challenges and open problems encountered in the future IRS empowered THz communications are also highlighted.Concretely,these emerging problems possibly originate from channel modeling,new material exploration,experimental IRS testbeds and intensive deployment.Ultimately,the combination of THz communications and IRS is capable of accelerating the development of 6G wireless networks.
基金This work was supported by the U.K.Engineering and Physical Sciences Research Council under Grants EP/P008402/2 and EP/R001588/1.
文摘In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.
基金supported by the National Key R&D Program of China under grant 2018YFB1801101 and 2016YFB0502202Zhejiang Lab(No.2019LC0AB02),NSFC projects(61971136,61601119,61960206005,and 61803211)+3 种基金Jiangsu NSF project(No.BK20191261)the Fundamental Research Funds for the Central UniversitiesYoung Elite Scientist Sponsorship Program by CAST(YESS20160042)Zhishan Youth Scholar Program of SEU。
文摘A joint beamforming algorithm is proposed for intelligent reflecting surface(IRS) aided wireless multiple-input multiple-output(MIMO) communication using statistical channel state information(CSI). The beamforming is done by alternatively optimizing the IRS reflecting coefficients and the covariance matrix of the transmit symbol vector, such that the ergodic rate of the system is maximized. The algorithm utilizes only the second order momentum of the random channel matrices and does assume any specific channel distribution, leading to a general framework for ergodic rate evaluation. A practical channel correlation model is configured to validate the performance gain. It is found that the rate can be enlarged by the joint optimization algorithm, however, the gain over that of randomly deployed reflecting coefficients depends highly on the relative correlation distance of the IRS elements and the spatial position of the IRS. In particular, the results suggest that IRS should be placed in the vicinity of either the transmitter or the receiver. Placing IRS far away from those positions is non-beneficial.
基金supported in part by the National Natural Science Foundation of China under Grants 62071234,61901121 and 61771244in part by the Natural Science Research Project of Education Department of Anhui Province of China under Grant KJ2019A1002.
文摘This paper considers a secure multigroup multicast multiple-input single-output(MISO)communication system aided by an intelligent reflecting surface(IRS).Specifically,we aim to minimize the transmit power at Alice via jointly optimizing the transmit beamformer,artificial noise(AN)vector and phase shifts at the IRS subject to the secrecy rate constraints as well as the unit modulus constraints of IRS phase shifts.To tackle the optimization problem,we first transform it into a semidefinite relaxation(SDR)problem,and then alternately update the transmit beamformer and AN matrix as well as the phase shifts at the IRS.In order to reduce the high computational complexity,we further propose a low-complexity algorithm based on second-order cone programming(SOCP).We decouple the optimization problem into two sub-problems and optimize the transmit beamformer,AN vector and the phase shifts alternately by solving two corresponding SOCP subproblem.Simulation results show that the proposed SDR and SOCP schemes require half or less transmit power than the scheme without IRS,which demonstrates the advantages of introducing IRS and the effectiveness of the proposed methods.
基金supported in part by National Natural Science Foundation of China under Grants 62122069, 62072490, 62071431, and 61871271in part by Science and Technology Development Fund of Macao SAR under Grants 0060/2019/A1 and 0162/2019/A3+5 种基金in part by FDCT-MOST Joint Project under Grant 0066/2019/AMJin part by the Intergovernmental International Cooperation in Science and Technology Innovation Program under Grant 2019YFE0111600in part by FDCT SKL-IOTSC(UM)-2021-2023in part by Zhejiang Provincial Natural Science Foundation of China under Grant LR17F010002in part by the Shenzhen Science and Technology Program under Projects JCYJ20210324093011030 and JCYJ20190808120415286in part by Research Grant of University of Macao under Grants MYRG2020-00107-IOTSC and SRG201900168-IOTSC。
文摘Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread attention.However, the process of FL involves frequent communications between the server and mobile devices,which incurs a long latency. Intelligent reflecting surface(IRS) provides a promising technology to address this issue, thanks to its capacity to reconfigure the wireless propagation environment. In this paper, we exploit the advantage of IRS to reduce the latency of FL. Specifically, we formulate a latency minimization problem for the IRS assisted FL system, by optimizing the communication resource allocations including the devices’ transmit-powers, the uploading time, the downloading time, the multi-user decomposition matrix and the phase shift matrix of IRS. To solve this non-convex problem, we propose an efficient algorithm which is based on the Block Coordinate Descent(BCD) and the penalty difference of convex(DC) algorithm to compute the solution. Numerical results are provided to validate the efficiency of our proposed algorithm and demonstrate the benefit of deploying IRS for reducing the latency of FL. In particular, the results show that our algorithm can outperform the baseline of Majorization-Minimization(MM) algorithm with the fixed transmit-power by up to 30%.
基金supported in part by the the National Key Research and Development Program of China under No.2019YFB1803200by the National Natural Science Foundation of China(NSFC)under Grant 61620106001 and 61901034.
文摘Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.
基金supported by the Fundamental Research Funds for the Central Universities(No.FRF-TP-20-106A1)。
文摘The performance of symbiotic radio(SR)networks can be improved by equipping secondary transmitters(STs)with intelligent reflecting surfaces(IRSs).Since the IRS power consumption is a non-negligible issue for STs,we consider an IRS assisted SR system where the IRS operates under power splitting(PS)mode.We aim at minimizing the IRS power consumption for the ST under the quality of service constraints for both primary and secondary transmissions by optimizing the transmit beamforming,the reflect beamforming and the PS factor.The optimization problem is non-convex.To tackle it,an algorithm is proposed by employing the block coordinate descent,semidefinite relaxation and alternating direction method of multipliers techniques.Simulation results demonstrate the efficiency and effectiveness of the proposed algorithm.
文摘The new requirements from the 5<sup>th</sup> and the 6<sup>th</sup> generation of wireless communication are ultra-high data rate, energy efficiency, wide coverage and connectivity, high reliability, and low latency. The current technologies cannot achieve all the mentioned requirements. New technologies and new approaches for deploying more active and passive nodes must be developed. Furthermore, the use of MMW band and THz band (30 - 300 GHz), in order to utilize their huge bandwidth, results in deploying more active node and more antennas due to high propagation losses and “LOS” behavior at this band. Development of innovative technologies is necessary to realize the above demand for growth of future wireless communication. The main task is to suggest solutions for the time varying characteristic of the wireless channel due to the user mobility and shadowing or blocking of communication channel. The current methods such as use of pilot channel to estimate the fading, various modulation or coding and beamforming, have overhead and limitations over random (large, unexpected changes) channels.
文摘In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(IRS),we propose a deep learning-based channel estimation scheme.The proposed scheme employs a hybrid active/passive IRS architecture,wherein the least square(LS)algorithm is initially utilized to acquire the channel estimate from the active elements.Subsequently,this estimation is interpolated to obtain a preliminary channel estimation and ultimately refined into an accurate estimate of the channel using the channel super-resolution convolutional neural network(Chan-SRCNN)deep learning network.The simulation results demonstrate that the proposed scheme surpasses LS,orthogonal matching pursuit(OMP),synchronous OMP(SOMP),and deep neural network(DNN)channel estimation algorithms in terms of normalized mean squared error(NMSE)performance,thereby validating the feasibility of the proposed approach.
文摘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.
基金the National Natural Science Foundation of China under Grants 62001517 and 61971474the Beijing Nova Program under Grant Z201100006820121.
文摘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.
基金funding from the Australian Government,via grant AUSMURIB000001 associated with ONR MURI Grant N00014-19-1-2571。
文摘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.
基金supported in part by the Key Scientific and Technological Project of Henan Province(Grant Nos.212102210558,222102210212)Doctoral Research Start Project of Henan Institute of Technology(Grant No.KQ1852).
文摘This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communication.With the popularization of UAV technology,more and more communication scenarios need UAV support.We consider using IRS to improve the secrecy efficiency.Specifically,IRS and UAV trajectories work together to counter potential eavesdroppers,while balancing the secrecy rate and energy consumption.The original problem is difficult to solve due to the coupling of optimization variables.We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem,and then prove the equivalence between relaxation problem and the original problem.Then an iterative algorithm is proposed by applying the block coordinate descent(BCD)method and the inner approximationmethod.The simulation results show that the proposed algorithm converges fast and is superior to the existing schemes.In addition,in order to improve the robustness of the algorithm,we also pay attention to the case of obtaining imperfect channel state information(CSI).
基金supported in part by the Shenzhen Basic Research Program under Grant 20200811192821001 and JCYJ20190808122409660in part by the Guangdong Basic Research Program under Grant 2019A1515110358,2021A1515012097,2020ZDZX1037,2020ZDZX1021+1 种基金in part by the open research fund of National Mobile Communications Research LaboratorySoutheast University under Grant 202ID 16,the key Project of DEGP under Grant 2018KCXTD027.
文摘Intelligent reflecting surface(IRS)is a revolutionizing and promising technology to improve the high transmission rate of the wireless communication systems.Specifically,an IRS consists of a great amount of low-cost passive reflecting elements,which reflect the incident signals to the desired user by collaboratively using passive beamforming.This paper introduces IRSs into a device-to-device(D2D)underlying cellular system to enhance transmission rate performance of the D2D pairs.We formulate an optimization problem of maximizing the transmission rate of the D2D pairs while satisfying the minimum required rate of the cellular users.We address this problem by jointly optimizing the reuse indicator,received beamforming,power allocation,and phase shift matrices.Block coordinate descent(BCD)algorithm is adopted to decouple the original problem into four subproblems.Closed form solutions are obtained by solving the sub-problems of optimizing the received beamforming and power allocation.Then,Kuhn-Munkres(KM)algorithm and minimization-majorization(MM)algorithm are adopted to solve the sub-problems of optimizing the reuse indicator and phase shift matrices,respectively.Simulation results demonstrate that IRSs can effectively improve the transmission rate of the D2D pairs and our proposed distributed IRSs scheme outperforms the other benchmark schemes.
