This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving ...This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving transmission signals from Uplink(UL)users and echo signal from target,while communicating with Downlink(DL)users and simultaneously detecting target.With the objective of maximizing the Average Sum Rate(ASR)for both UL and DL users,a composite non-convex optimization problem is established,which is decomposed into sub-problems of communication scheduling optimization,transceiver beamforming design,and UAV trajectory optimization.An alternating iterative algorithm is proposed,employing relaxation optimization,extremum traversal search,augmented weighted minimum mean square error,and successive convex approximation methods to solve the aforementioned sub-problems.Simulation results demonstrate that,compared to the traditional UAV-assisted Half-Duplex(HD)ISAC scheme,the proposed FD ISAC scheme effectively improves the ASR.展开更多
Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory des...Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory design,and resource allocation for energy-efficient aerial networked systems with the aid of an integrated sensing and communications(ISAC)framework,in which multiple UAVs are employed to simultaneously conduct cooperative sensing and covert downlink transmissions to multiple ground users(GUs)in the presence of a mobile warden(Willie).Specifically,to improve the communication covertness,UAVs are strategically switched between jamming(JUAV)and information(IUAV)modes.Additionally,to cope with the mobility of Willie,an unscented Kalman filtering(UKF)-based method is employed to track and predict Willie’s location relying on the delay and Doppler measurements extracted from the ISAC echoes.Capitalizing on the predicted Willie’s location,a real-time energy efficiency(EE)maximization problem is formulated by jointly optimizing the JUAV selection strategy,IUAV-GU scheduling,communication/jamming power allocation,and UAV trajectories design.The formulation takes into account the communication covertness requirement and the maximum transmit power budget,leading to a mixed-integer non-convex fractional programming.To tackle this challenge,the alternating optimization(AO)approach is adopted,which decomposes the original problem into a series of sub-problems,allowing us to obtain an efficient sub-optimal solution.Simulation results demonstrate that the proposed scheme is capable of tracking Willie accurately and offering excellent system EE performance compared to various benchmark schemes adopting existing designs.展开更多
通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题...通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题,仍是具有挑战性的难题。为此,提出了一种基于子阵列的混合波束赋形设计方案,在较低的硬件复杂度下通过扩展球面波区域范围提供距离维增益,以在满足感知性能约束和发射功率预算的前提下最大化通信速率。首先提出了一种基于分式规划和最优化最小化方法的算法,将非凸优化问题转化为凸问题后迭代求解得到一个联合波束赋形矩阵;进而提出一种基于流形优化和最小二乘法的算法,迭代求解后将其分解为数字/模拟波束赋形矩阵。仿真结果表明,基于子阵列的算法相较于集中式阵列能够获得更多的距离维信息和感知自由度,通信性能提升40%,且流形优化后混合波束赋形方案能够很好地逼近联合优化的数字波束赋形方案的性能。展开更多
This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrate...This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.展开更多
Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably incr...Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably increases computing demands,risking real-time system stability.Vehicle Edge Computing(VEC)addresses this by offloading tasks to Road Side Units(RSUs),ensuring timely services.Our previous work,the FLSimCo algorithm,which uses local resources for federated Self-Supervised Learning(SSL),has a limitation:vehicles often can’t complete all iteration tasks.Our improved algorithm offloads partial tasks to RSUs and optimizes energy consumption by adjusting transmission power,CPU frequency,and task assignment ratios,balancing local and RSU-based training.Meanwhile,setting an offloading threshold further prevents inefficiencies.Simulation results show that the enhanced algorithm reduces energy consumption and improves offloading efficiency and accuracy of federated SSL.展开更多
Integrated sensing and communication(ISAC),assisted by reconfigurable intelligent surface(RIS)has emerged as a breakthrough technology to improve the capacity and reliability of 6G wireless network.However,a significa...Integrated sensing and communication(ISAC),assisted by reconfigurable intelligent surface(RIS)has emerged as a breakthrough technology to improve the capacity and reliability of 6G wireless network.However,a significant challenge in RIS-ISAC systems is the acquisition of channel state information(CSI),largely due to co-channel interference,which hinders meeting the required reliability standards.To address this issue,a minimax-concave penalty(MCP)-based CSI refinement scheme is proposed.This approach utilizes an element-grouping strategy to jointly estimate the ISAC channel and the RIS phase shift matrix.Unlike previous methods,our scheme exploits the inherent sparsity in RIS-assisted ISAC channels to reduce training overhead,and the near-optimal solution is derived for our studied RIS-ISAC scheme.The effectiveness of the element-grouping strategy is validated through simulation experiments,demonstrating superior channel estimation results when compared to existing benchmarks.展开更多
Advancements in mode-division multiplexing(MDM)techniques,aimed at surpassing the Shannon limit and augmenting transmission capacity,have garnered significant attention in optical fiber communica-tion,propelling the d...Advancements in mode-division multiplexing(MDM)techniques,aimed at surpassing the Shannon limit and augmenting transmission capacity,have garnered significant attention in optical fiber communica-tion,propelling the demand for high-quality multiplexers and demultiplexers.However,the criteria for ideal-mode multiplexers/demultiplexers,such as performance,scalability,compatibility,and ultra-compactness,have only partially been achieved using conventional bulky devices(e.g.,waveguides,grat-ings,and free space optics)—an issue that will substantially restrict the application of MDM techniques.Here,we present a neuro-meta-router(NMR)optimized through deep learning that achieves spatial multi-mode division and supports multi-channel communication,potentially offering scalability,com-patibility,and ultra-compactness.An MDM communication system based on an NMR is theoretically designed and experimentally demonstrated to enable simultaneous and independent multi-dataset transmission,showcasing a capacity of up to 100 gigabits per second(Gbps)and a symbol error rate down to the order of 104,all achieved without any compensation technologies or correlation devices.Our work presents a paradigm that merges metasurfaces,fiber communications,and deep learning,with potential applications in intelligent metasurface-aided optical interconnection,as well as all-optical pat-tern recognition and classification.展开更多
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(...In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.展开更多
With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of...With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of 5G/6G networks will inevitably lead to severe interference,resulting in degradation in the communication performance of maritime users.In this paper,we propose a safe deep reinforcement learning based interference coordination scheme to jointly optimize the power control and bandwidth allocation in maritime communication systems,and exploit the quality-of-service requirements of users as the risk value references to evaluate the communication policies.In particular,this scheme designs a deep neural network to select the communication policies through the evaluation network and update the parameters using the target network,which improves the communication performance and speeds up the convergence rate.Moreover,the Nash equilibrium of the interference coordination game and the computational complexity of the proposed scheme are analyzed.Simulation and experimental results verify the performance gain of the proposed scheme compared with benchmarks.展开更多
The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport ...The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.展开更多
This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground commu...This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.展开更多
Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investig...Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.展开更多
This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passi...This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passive sensing scheme.The scheme is based on the radio frequency(RF)fingerprint learning of the RF radio unit(RRU)to build an RF fingerprint library of RRUs.The source RRU is identified by comparing the RF fingerprints carried by the signal at the receiver side.The receiver extracts the channel parameters from the signal and estimates the channel environment,thus locating the reflectors in the environment.The proposed scheme can effectively solve the problem of interference between signals in the same time-frequency domain but in different spatial domains when multiple RRUs jointly serve users in CF-RAN architecture.Simulation results show that the proposed passive ISAC scheme can effectively detect reflector location information in the environment without degrading the communication performance.展开更多
基金supported in part by Sub Project of National Key Research and Development Plan in 2020.NO.2020YFC1511704Beijing Information Science&Technology University.NO.2020KYNH212,NO.2021CGZH302+1 种基金Beijing Science and Technology Project(Grant No.Z211100004421009)in part by the National Natural Science Foundation of China(Grant No.62301058).
文摘This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving transmission signals from Uplink(UL)users and echo signal from target,while communicating with Downlink(DL)users and simultaneously detecting target.With the objective of maximizing the Average Sum Rate(ASR)for both UL and DL users,a composite non-convex optimization problem is established,which is decomposed into sub-problems of communication scheduling optimization,transceiver beamforming design,and UAV trajectory optimization.An alternating iterative algorithm is proposed,employing relaxation optimization,extremum traversal search,augmented weighted minimum mean square error,and successive convex approximation methods to solve the aforementioned sub-problems.Simulation results demonstrate that,compared to the traditional UAV-assisted Half-Duplex(HD)ISAC scheme,the proposed FD ISAC scheme effectively improves the ASR.
基金supported in part by the National Natural Science Foundation of China(Nos.62101232 and 62471208)in part by the Guangdong Provincial Natural Science Foundation,China(No.2024A151510098)+4 种基金in part by the Shenzhen Science and Technology Program,China(No.JCYJ20220530114412029)in part by Shenzhen Key Laboratory of Robotics and Computer Vision,China(No.ZDSYS20220330160557001)supported by the National Natural Science Foundation of China(No.62301206)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F010005)the Starting Research Fund from the Hangzhou Normal University,China(No.4115C50222204114).
文摘Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory design,and resource allocation for energy-efficient aerial networked systems with the aid of an integrated sensing and communications(ISAC)framework,in which multiple UAVs are employed to simultaneously conduct cooperative sensing and covert downlink transmissions to multiple ground users(GUs)in the presence of a mobile warden(Willie).Specifically,to improve the communication covertness,UAVs are strategically switched between jamming(JUAV)and information(IUAV)modes.Additionally,to cope with the mobility of Willie,an unscented Kalman filtering(UKF)-based method is employed to track and predict Willie’s location relying on the delay and Doppler measurements extracted from the ISAC echoes.Capitalizing on the predicted Willie’s location,a real-time energy efficiency(EE)maximization problem is formulated by jointly optimizing the JUAV selection strategy,IUAV-GU scheduling,communication/jamming power allocation,and UAV trajectories design.The formulation takes into account the communication covertness requirement and the maximum transmit power budget,leading to a mixed-integer non-convex fractional programming.To tackle this challenge,the alternating optimization(AO)approach is adopted,which decomposes the original problem into a series of sub-problems,allowing us to obtain an efficient sub-optimal solution.Simulation results demonstrate that the proposed scheme is capable of tracking Willie accurately and offering excellent system EE performance compared to various benchmark schemes adopting existing designs.
文摘通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题,仍是具有挑战性的难题。为此,提出了一种基于子阵列的混合波束赋形设计方案,在较低的硬件复杂度下通过扩展球面波区域范围提供距离维增益,以在满足感知性能约束和发射功率预算的前提下最大化通信速率。首先提出了一种基于分式规划和最优化最小化方法的算法,将非凸优化问题转化为凸问题后迭代求解得到一个联合波束赋形矩阵;进而提出一种基于流形优化和最小二乘法的算法,迭代求解后将其分解为数字/模拟波束赋形矩阵。仿真结果表明,基于子阵列的算法相较于集中式阵列能够获得更多的距离维信息和感知自由度,通信性能提升40%,且流形优化后混合波束赋形方案能够很好地逼近联合优化的数字波束赋形方案的性能。
基金supported in part by the National Natural Science Foundation of China under Grant U21B2014,Grant 92267202,and Grant 62271081.
文摘This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.
文摘Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably increases computing demands,risking real-time system stability.Vehicle Edge Computing(VEC)addresses this by offloading tasks to Road Side Units(RSUs),ensuring timely services.Our previous work,the FLSimCo algorithm,which uses local resources for federated Self-Supervised Learning(SSL),has a limitation:vehicles often can’t complete all iteration tasks.Our improved algorithm offloads partial tasks to RSUs and optimizes energy consumption by adjusting transmission power,CPU frequency,and task assignment ratios,balancing local and RSU-based training.Meanwhile,setting an offloading threshold further prevents inefficiencies.Simulation results show that the enhanced algorithm reduces energy consumption and improves offloading efficiency and accuracy of federated SSL.
基金supported in part by the National Natural Science Foundation of China under Grant 62001171in part by the Natural Science Foundation of Guangdong Province under Grant 2024A1515011172in part by the Henan Science and Technology Research and Development Program Joint Fund under Grant 235200810049。
文摘Integrated sensing and communication(ISAC),assisted by reconfigurable intelligent surface(RIS)has emerged as a breakthrough technology to improve the capacity and reliability of 6G wireless network.However,a significant challenge in RIS-ISAC systems is the acquisition of channel state information(CSI),largely due to co-channel interference,which hinders meeting the required reliability standards.To address this issue,a minimax-concave penalty(MCP)-based CSI refinement scheme is proposed.This approach utilizes an element-grouping strategy to jointly estimate the ISAC channel and the RIS phase shift matrix.Unlike previous methods,our scheme exploits the inherent sparsity in RIS-assisted ISAC channels to reduce training overhead,and the near-optimal solution is derived for our studied RIS-ISAC scheme.The effectiveness of the element-grouping strategy is validated through simulation experiments,demonstrating superior channel estimation results when compared to existing benchmarks.
基金supported by the National Key Research and Development Program of China(2023YFB2804704)the National Natural Science Foundation of China(12174292,12374278,and 62105250).
文摘Advancements in mode-division multiplexing(MDM)techniques,aimed at surpassing the Shannon limit and augmenting transmission capacity,have garnered significant attention in optical fiber communica-tion,propelling the demand for high-quality multiplexers and demultiplexers.However,the criteria for ideal-mode multiplexers/demultiplexers,such as performance,scalability,compatibility,and ultra-compactness,have only partially been achieved using conventional bulky devices(e.g.,waveguides,grat-ings,and free space optics)—an issue that will substantially restrict the application of MDM techniques.Here,we present a neuro-meta-router(NMR)optimized through deep learning that achieves spatial multi-mode division and supports multi-channel communication,potentially offering scalability,com-patibility,and ultra-compactness.An MDM communication system based on an NMR is theoretically designed and experimentally demonstrated to enable simultaneous and independent multi-dataset transmission,showcasing a capacity of up to 100 gigabits per second(Gbps)and a symbol error rate down to the order of 104,all achieved without any compensation technologies or correlation devices.Our work presents a paradigm that merges metasurfaces,fiber communications,and deep learning,with potential applications in intelligent metasurface-aided optical interconnection,as well as all-optical pat-tern recognition and classification.
基金supported by Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
基金supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-035Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2.
文摘In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.
文摘With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of 5G/6G networks will inevitably lead to severe interference,resulting in degradation in the communication performance of maritime users.In this paper,we propose a safe deep reinforcement learning based interference coordination scheme to jointly optimize the power control and bandwidth allocation in maritime communication systems,and exploit the quality-of-service requirements of users as the risk value references to evaluate the communication policies.In particular,this scheme designs a deep neural network to select the communication policies through the evaluation network and update the parameters using the target network,which improves the communication performance and speeds up the convergence rate.Moreover,the Nash equilibrium of the interference coordination game and the computational complexity of the proposed scheme are analyzed.Simulation and experimental results verify the performance gain of the proposed scheme compared with benchmarks.
基金National Natural Science Foundation of China(U2468201,62122012,62221001).
文摘The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.
基金supported by the National Natural Science Foundation of China(No.62371080 and 62031006)the National Science Foundation of Chongqing,China(No.CSTB2022NSCQ-MSX0597)the Venture&Innovation Support Program for Chongqing Overseas Returnees,China(No.cx2022063)。
文摘This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.
文摘Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.
基金supported in part by the National Key Research and Development Program under Grant(2021YFB2900300)by the National Natural Science Foundation of China(NSFC)under Grants 61971127,61871122by the Southeast University-China Mobile Research Institute Joint Innovation Center,and by the Major Key Project of PCL(PCL2021A01-2).
文摘This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passive sensing scheme.The scheme is based on the radio frequency(RF)fingerprint learning of the RF radio unit(RRU)to build an RF fingerprint library of RRUs.The source RRU is identified by comparing the RF fingerprints carried by the signal at the receiver side.The receiver extracts the channel parameters from the signal and estimates the channel environment,thus locating the reflectors in the environment.The proposed scheme can effectively solve the problem of interference between signals in the same time-frequency domain but in different spatial domains when multiple RRUs jointly serve users in CF-RAN architecture.Simulation results show that the proposed passive ISAC scheme can effectively detect reflector location information in the environment without degrading the communication performance.
