In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of ...In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.展开更多
Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning mas...Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning massive reflecting elements.This paper considers a distributed IRS aided decode-and-forward(DF)relaying system over Nakagami-m fading channels.Based on a tight approximation for the distribution of the received signalto-noise ratio(SNR),we first derive exact closed-form expressions of the outage probability,ergodic capacity,and energy efficiency for the considered system.Moreover,we propose the optimal IRS configuration considering the energy efficiency and pilot overhead.Finally,we compare the performance between the distributed IRS-aided DF relaying and multi-IRS-only systems,and verify the analytical results by using monte carlo simulations.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
In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET...In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.展开更多
The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance th...The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.展开更多
The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of...The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel conditions.However,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex problem.This paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)systems.The proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by one.The results show that the proposed method has better performance than that of the randomized IRS systems.The number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.展开更多
The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of e...The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of employing intelligent reflective surfaces(IRS)andUAVs as relay nodes to efficiently offload user computing tasks to theMEC server system model.Specifically,the user node accesses the primary user spectrum,while adhering to the constraint of satisfying the primary user peak interference power.Furthermore,the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes,namely time switching(TS)and power splitting(PS).The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio.Subsequently,the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed.The study investigates the impact of various system parameters,including the number of UAVs,peak interference power,TS,and PS factors,on the system’s outage performance through simulation.The proposed system is also compared to two conventional benchmark schemes:the optimal UAV link transmission and the IRS link transmission.The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes.展开更多
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
In this paper,we investigate the energy efficiency maximization for mobile edge computing(MEC)in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communications.In particular,UAVcan collect the ...In this paper,we investigate the energy efficiency maximization for mobile edge computing(MEC)in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communications.In particular,UAVcan collect the computing tasks of the terrestrial users and transmit the results back to them after computing.We jointly optimize the users’transmitted beamforming and uploading ratios,the phase shift matrix of IRS,and the UAV trajectory to improve the energy efficiency.The formulated optimization problem is highly non-convex and difficult to be solved directly.Therefore,we decompose the original problem into three sub-problems.We first propose the successive convex approximation(SCA)based method to design the beamforming of the users and the phase shift matrix of IRS,and apply the Lagrange dual method to obtain a closed-form expression of the uploading ratios.For the trajectory optimization,we propose a block coordinate descent(BCD)based method to obtain a local optimal solution.Finally,we propose the alternating optimization(AO)based overall algorithmand analyzed its complexity to be equivalent or lower than existing algorithms.Simulation results show the superiority of the proposedmethod compared with existing schemes in energy efficiency.展开更多
Cholesteric liquid crystals(CLCs) have recently sparked an enormous amount of interest in the development of soft matter materials due to their unique ability to self-organize into a helical supra-molecular architec...Cholesteric liquid crystals(CLCs) have recently sparked an enormous amount of interest in the development of soft matter materials due to their unique ability to self-organize into a helical supra-molecular architecture and their excellent selective reflection of light based on the Bragg relationship.Nowadays,by the virtue of building the self-organized nanostructures with pitch gradient or non-uniform pitch distribution,extensive work has already been performed to obtain CLC films with a broad reflection band.Based on authors' many years' research experience,this critical review systematically summarizes the physical and optical background of the CLCs with broadband reflection characteristics,methods to obtain broadband reflection of CLCs,as well as the application in the field of intelligent optical modulation materials.Combined with the research status and the advantages in the field,the important basic and applied scientific problems in the research direction are also introduced.展开更多
Hardware impairments(HI)are always present in low-cost wireless devices.This paper investigates the outage behaviors of intelligent reflecting surface(IRS)assisted non-orthogonal multiple access(NOMA)networks by takin...Hardware impairments(HI)are always present in low-cost wireless devices.This paper investigates the outage behaviors of intelligent reflecting surface(IRS)assisted non-orthogonal multiple access(NOMA)networks by taking into account the impact of HI.Specifically,we derive the approximate and asymptotic expressions of the outage probability for the IRS-NOMA-HI networks.Based on the asymptotic results,the diversity orders under perfect self-interference cancellation and imperfect self-interference cancellation scenarios are obtained to evaluate the performance of the considered network.In addition,the system throughput of IRS-NOMA-HI is discussed in delay-limited mode.The obtained results are provided to verify the accuracy of the theoretical analyses and reveal that:1)The outage performance and system throughput for IRS-NOMA-HI outperforms that of the IRS-assisted orthogonal multiple access-HI(IRS-OMA-HI)networks;2)The number of IRS elements,the pass loss factors,the Rician factors,and the value of HI are pivotal to enhancing the performance of IRS-NOMAHI networks;and 3)It is recommended that effective methods of reducing HI should be used to ensure system performance,in addition to self-interference cancellation techniques.展开更多
Covert communications can hide the existence of a transmission from the transmitter to receiver.This paper considers an intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)covert communication syst...Covert communications can hide the existence of a transmission from the transmitter to receiver.This paper considers an intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)covert communication system.It was inspired by the high-dimensional data processing and decisionmaking capabilities of the deep reinforcement learning(DRL)algorithm.In order to improve the covert communication performance,an UAV 3D trajectory and IRS phase optimization algorithm based on double deep Q network(TAP-DDQN)is proposed.The simulations show that TAP-DDQN can significantly improve the covert performance of the IRS-assisted UAV covert communication system,compared with benchmark solutions.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,a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer(SWIPT)aided sensor networks is developed for active beamforming of multiante...In this paper,a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer(SWIPT)aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces(IRS).By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS,we aimtomaximize the minimumharvested energy efficiency among all the energy receivers(ER)where information receivers(IR)are bound to the signal-interference-noise-ratio(SINR)and the maximum transmitted power of the transmitter.To handle the non-convex problem,both semi-definite relaxation(SDR)and block coordinate descent technologies are exploited.Then,the original problem is transformed into two convex sub-problems which can be solved via semidefinite programming.Numerical simulation results demonstrate that the IRS and energy beamformer settings in this paper provide greater system gain than the traditional experimental setting,thereby improving the fairness-aware harvested energy efficiency of the ER.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
Effective resource allocation can exploit the advantage of intelligent reflective surface(IRS)assisted mobile edge computing(MEC)fully.However,it is challenging to balance the limited energy of MTs and the strict dela...Effective resource allocation can exploit the advantage of intelligent reflective surface(IRS)assisted mobile edge computing(MEC)fully.However,it is challenging to balance the limited energy of MTs and the strict delay requirement of their tasks.In this paper,in order to tackle the challenge,we jointly optimize the offloading delay and energy consumption of mobile terminals(MTs)to realize the delay-energy tradeoff in an IRS-assisted MEC network,in which non-orthogonal multiple access(NOMA)and multiantenna are applied to improve spectral efficiency.To achieve the optimal delay-energy tradeoff,an offloading cost minimization model is proposed,in which the edge computing resource allocation,signal detecting vector,uplink transmission power,and IRS phase shift coefficient are needed to be jointly optimized.The optimization of the model is a multi-level fractional problem in complex fields with some coupled high dimension variables.To solve the intractable problem,we decouple the original problem into a computing subproblem and a wireless transmission subproblem based on the uncoupled relationship between different variable types.The computing subproblem is proved convex and the closed-form solution is obtained for the edge computing resource allocation.Further,the wireless transmission subproblem is solved iteratively through decoupling the residual variables.In each iteration,the closed-form solution of residual variables is obtained through different successive convex approximation(SCA)methods.We verify the proposed algorithm can converge to an optimum with polynomial complexity.Simulation results indicate the proposed method achieves average saved costs of 65.64%,11.24%,and 9.49%over three benchmark methods respectively.展开更多
Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper propose...Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer(SWIPT)in a cognitive radio network(CRN).Here,the base station(BS)utilizes spectrum assigned to the primary users(PUs)to simultaneously serve multiple energy receivers(ERs)and information receivers(IRs)through IRS-aided multicast technology.In particular,by assuming that only the imperfect channel state information(CSI)is available,we first formulate a constrained problem to maximize the minimal achievable rate of IRs,while satisfying the harvesting energy threshold of ERs,the quality-of-service requirement of IRs,the interference threshold of PUs and transmit power budget of BS.To address the non-convex problem,we then adopt triangle inequality to deal with the channel uncertainty,and propose a low-complexity algorithm combining alternating direction method of multipliers(ADMM)with alternating optimi-zation(AO)to jointly optimize the active and passive beamformers for the BS and IRS,respectively.Finally,our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.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
基金This work was supported by the Key Scientific and Technological Project of Henan Province(Grant Number 222102210212)Doctoral Research Start Project of Henan Institute of Technology(Grant Number KQ2005)Key Research Projects of Colleges and Universities in Henan Province(Grant Number 23B510006).
文摘In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.
基金supported in part by National Natural Science Foundation of China under Grant 62371262 and 61971467in part by the Key Research and Development Program of Jiangsu Province of China under Grant BE2021013-1+1 种基金in part by the Qinlan Project of Jiangsu Provincein part by the Scientific Research Program of Nantong under Grant JC22022026
文摘Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning massive reflecting elements.This paper considers a distributed IRS aided decode-and-forward(DF)relaying system over Nakagami-m fading channels.Based on a tight approximation for the distribution of the received signalto-noise ratio(SNR),we first derive exact closed-form expressions of the outage probability,ergodic capacity,and energy efficiency for the considered system.Moreover,we propose the optimal IRS configuration considering the energy efficiency and pilot overhead.Finally,we compare the performance between the distributed IRS-aided DF relaying and multi-IRS-only systems,and verify the analytical results by using monte carlo simulations.
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This work was supported in part by the open research fund of National Mobile Communications Research Laboratory,Southeast University(No.2023D11)in part by Sponsored by program for Science&Technology Innovation Talents in Universities of Henan Province(23HASTIT019)+2 种基金in part by Natural Science Foundation of Henan Province(20232300421097)in part by the project funded by China Postdoctoral Science Foundation(2020M682345)in part by the Henan Postdoctoral Foundation(202001015).
文摘In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 62271099。
文摘The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2022-2018-0-01423)supervised by the ITP(Institute for Information&Communications Technology Planning&Evaluation)supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2020R1A6A1A03038540).
文摘The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel conditions.However,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex problem.This paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)systems.The proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by one.The results show that the proposed method has better performance than that of the randomized IRS systems.The number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.
基金the National Natural Science Foundation of China(62271192)Henan Provincial Scientists Studio(GZS2022015)+10 种基金Central Plains Talents Plan(ZYYCYU202012173)NationalKeyR&DProgramofChina(2020YFB2008400)the Program ofCEMEE(2022Z00202B)LAGEO of Chinese Academy of Sciences(LAGEO-2019-2)Program for Science&Technology Innovation Talents in the University of Henan Province(20HASTIT022)Natural Science Foundation of Henan under Grant 202300410126Program for Innovative Research Team in University of Henan Province(21IRTSTHN015)Equipment Pre-Research Joint Research Program of Ministry of Education(8091B032129)Training Program for Young Scholar of Henan Province for Colleges and Universities(2020GGJS172)Program for Science&Technology Innovation Talents in Universities of Henan Province under Grand(22HASTIT020)Henan Province Science Fund for Distinguished Young Scholars(222300420006).
文摘The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of employing intelligent reflective surfaces(IRS)andUAVs as relay nodes to efficiently offload user computing tasks to theMEC server system model.Specifically,the user node accesses the primary user spectrum,while adhering to the constraint of satisfying the primary user peak interference power.Furthermore,the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes,namely time switching(TS)and power splitting(PS).The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio.Subsequently,the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed.The study investigates the impact of various system parameters,including the number of UAVs,peak interference power,TS,and PS factors,on the system’s outage performance through simulation.The proposed system is also compared to two conventional benchmark schemes:the optimal UAV link transmission and the IRS link transmission.The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes.
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the Key Scientific and Technological Project of Henan Province(Grant Number 222102210212)Doctoral Research Start Project of Henan Institute of Technology(Grant Number KQ2005)+1 种基金Doctoral Research Start Project of Henan Institute of Technology(Grant Number KQ2110)Key Research Projects of Colleges and Universities in Henan Province(Grant Number 23B510006).
文摘In this paper,we investigate the energy efficiency maximization for mobile edge computing(MEC)in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communications.In particular,UAVcan collect the computing tasks of the terrestrial users and transmit the results back to them after computing.We jointly optimize the users’transmitted beamforming and uploading ratios,the phase shift matrix of IRS,and the UAV trajectory to improve the energy efficiency.The formulated optimization problem is highly non-convex and difficult to be solved directly.Therefore,we decompose the original problem into three sub-problems.We first propose the successive convex approximation(SCA)based method to design the beamforming of the users and the phase shift matrix of IRS,and apply the Lagrange dual method to obtain a closed-form expression of the uploading ratios.For the trajectory optimization,we propose a block coordinate descent(BCD)based method to obtain a local optimal solution.Finally,we propose the alternating optimization(AO)based overall algorithmand analyzed its complexity to be equivalent or lower than existing algorithms.Simulation results show the superiority of the proposedmethod compared with existing schemes in energy efficiency.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51573006,51573003,51203003,51303008,51302006,51402006,51272026,and 51273022)the Major Project of Beijing Science and Technology Program,China(Grant Nos.Z151100003315023 and Z141100003814011)the Fok Ying Tung Education Foundation,China(Grant No.142009)
文摘Cholesteric liquid crystals(CLCs) have recently sparked an enormous amount of interest in the development of soft matter materials due to their unique ability to self-organize into a helical supra-molecular architecture and their excellent selective reflection of light based on the Bragg relationship.Nowadays,by the virtue of building the self-organized nanostructures with pitch gradient or non-uniform pitch distribution,extensive work has already been performed to obtain CLC films with a broad reflection band.Based on authors' many years' research experience,this critical review systematically summarizes the physical and optical background of the CLCs with broadband reflection characteristics,methods to obtain broadband reflection of CLCs,as well as the application in the field of intelligent optical modulation materials.Combined with the research status and the advantages in the field,the important basic and applied scientific problems in the research direction are also introduced.
基金supported by the National Natural Science Foundation of China under Grants 62071052,61901043the R&D Program of Beijing Municipal Education Commission under Grant KM202011232003+1 种基金supported by Talent Engineering Training Funds of Hebei Province under Grant A202101106Science and Technology Project of Hebei Education Department under Grant QN2020508.
文摘Hardware impairments(HI)are always present in low-cost wireless devices.This paper investigates the outage behaviors of intelligent reflecting surface(IRS)assisted non-orthogonal multiple access(NOMA)networks by taking into account the impact of HI.Specifically,we derive the approximate and asymptotic expressions of the outage probability for the IRS-NOMA-HI networks.Based on the asymptotic results,the diversity orders under perfect self-interference cancellation and imperfect self-interference cancellation scenarios are obtained to evaluate the performance of the considered network.In addition,the system throughput of IRS-NOMA-HI is discussed in delay-limited mode.The obtained results are provided to verify the accuracy of the theoretical analyses and reveal that:1)The outage performance and system throughput for IRS-NOMA-HI outperforms that of the IRS-assisted orthogonal multiple access-HI(IRS-OMA-HI)networks;2)The number of IRS elements,the pass loss factors,the Rician factors,and the value of HI are pivotal to enhancing the performance of IRS-NOMAHI networks;and 3)It is recommended that effective methods of reducing HI should be used to ensure system performance,in addition to self-interference cancellation techniques.
文摘Covert communications can hide the existence of a transmission from the transmitter to receiver.This paper considers an intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)covert communication system.It was inspired by the high-dimensional data processing and decisionmaking capabilities of the deep reinforcement learning(DRL)algorithm.In order to improve the covert communication performance,an UAV 3D trajectory and IRS phase optimization algorithm based on double deep Q network(TAP-DDQN)is proposed.The simulations show that TAP-DDQN can significantly improve the covert performance of the IRS-assisted UAV covert communication system,compared with benchmark solutions.
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This work was supported in part by the Priority Academic Program Development of Jiangsu Higher Education,the National Natural Science Foundation of China under Grant No.62171119the Key Research and Development Plan ofXuzhou underGrant Nos.KC20027,KC18079+1 种基金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.
文摘In this paper,a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer(SWIPT)aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces(IRS).By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS,we aimtomaximize the minimumharvested energy efficiency among all the energy receivers(ER)where information receivers(IR)are bound to the signal-interference-noise-ratio(SINR)and the maximum transmitted power of the transmitter.To handle the non-convex problem,both semi-definite relaxation(SDR)and block coordinate descent technologies are exploited.Then,the original problem is transformed into two convex sub-problems which can be solved via semidefinite programming.Numerical simulation results demonstrate that the IRS and energy beamformer settings in this paper provide greater system gain than the traditional experimental setting,thereby improving the fairness-aware harvested energy efficiency of the ER.
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funded by 2020 Industrial Technology Foundation Public Service Platform Project(2020-0105-2-1)Foshan Science and Technology Innovation Special Fund Project(No.BK20AF004).
文摘Effective resource allocation can exploit the advantage of intelligent reflective surface(IRS)assisted mobile edge computing(MEC)fully.However,it is challenging to balance the limited energy of MTs and the strict delay requirement of their tasks.In this paper,in order to tackle the challenge,we jointly optimize the offloading delay and energy consumption of mobile terminals(MTs)to realize the delay-energy tradeoff in an IRS-assisted MEC network,in which non-orthogonal multiple access(NOMA)and multiantenna are applied to improve spectral efficiency.To achieve the optimal delay-energy tradeoff,an offloading cost minimization model is proposed,in which the edge computing resource allocation,signal detecting vector,uplink transmission power,and IRS phase shift coefficient are needed to be jointly optimized.The optimization of the model is a multi-level fractional problem in complex fields with some coupled high dimension variables.To solve the intractable problem,we decouple the original problem into a computing subproblem and a wireless transmission subproblem based on the uncoupled relationship between different variable types.The computing subproblem is proved convex and the closed-form solution is obtained for the edge computing resource allocation.Further,the wireless transmission subproblem is solved iteratively through decoupling the residual variables.In each iteration,the closed-form solution of residual variables is obtained through different successive convex approximation(SCA)methods.We verify the proposed algorithm can converge to an optimum with polynomial complexity.Simulation results indicate the proposed method achieves average saved costs of 65.64%,11.24%,and 9.49%over three benchmark methods respectively.
基金supported in part by the Key International Cooper-ation Research Project under Grant 61720106003in part by NUPTSF under Grant NY220111+1 种基金in part by NUPTSF under Grant NY221009in part by the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX22_0959.
文摘Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer(SWIPT)in a cognitive radio network(CRN).Here,the base station(BS)utilizes spectrum assigned to the primary users(PUs)to simultaneously serve multiple energy receivers(ERs)and information receivers(IRs)through IRS-aided multicast technology.In particular,by assuming that only the imperfect channel state information(CSI)is available,we first formulate a constrained problem to maximize the minimal achievable rate of IRs,while satisfying the harvesting energy threshold of ERs,the quality-of-service requirement of IRs,the interference threshold of PUs and transmit power budget of BS.To address the non-convex problem,we then adopt triangle inequality to deal with the channel uncertainty,and propose a low-complexity algorithm combining alternating direction method of multipliers(ADMM)with alternating optimi-zation(AO)to jointly optimize the active and passive beamformers for the BS and IRS,respectively.Finally,our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.
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).