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
With the rapid growth of the low-altitude economy,the demand for typical low-altitude ap-plications has accelerated the advancement of inte-grated sensing and communications(ISAC)networks.This paper begins by analyzin...With the rapid growth of the low-altitude economy,the demand for typical low-altitude ap-plications has accelerated the advancement of inte-grated sensing and communications(ISAC)networks.This paper begins by analyzing representative ap-plication scenarios to clarify the core requirements of the low-altitude economy for modern ISAC net-works.By investigating the distinctive characteris-tics of ISAC networks in low-altitude environments,it presents a comprehensive analysis of key challenges and identifies four major issues:challenges in pre-cise target detection,interference management,in-consistent sensing and communication coverage,and the complexity of air-ground coordination and han-dover.Based on fundamental theories and principles,the paper proposes corresponding solutions,encom-passing advanced technologies for precise target de-tection and recognition,high-reliability networked de-tection,robust interference management,and seamless air-ground collaboration.These solutions aim to es-tablish a solid foundation for the future development of intelligent low-altitude networks and ensure effec-tive support for emerging applications.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
As key technologies in 6G,Space-Air-Ground Integrated Networks(SAGIN)promises to provide seamless global coverage through a comprehensive,ubiquitous communication system,while Integrated Sensing and Communications(ISA...As key technologies in 6G,Space-Air-Ground Integrated Networks(SAGIN)promises to provide seamless global coverage through a comprehensive,ubiquitous communication system,while Integrated Sensing and Communications(ISAC)effectively addresses spectrum congestion by sharing spectrum resources and transceivers for simultaneous communication and sensing operations.However,existing ISAC research has primarily focused on terrestrial networks,with limited exploration of its applications in SAGIN environments.This paper proposes a novel SAGIN-ISAC scheme leveraging High-Altitude Platform Stations(HAPS).In this scheme,HAPS serves as a relay node that not only amplifies and forwards communication signals but also receives and processes target echo signals for parameter estimation.The satellite employs Resilient Massive Access(RMA)to provide communication services to different User Terminals(UTs).To address scenarios with an unknown number of targets,we develop a Two-threshold Detection and Parameter Multiple Signal Classification(MUSIC)algorithm(TDPM),which employs dual-threshold correlation detection to determine the number of targets and utilizes the MUSIC algorithm to estimate targets’Angle of Arrival(AoA),range,and relative velocity.Furthermore,we establish a joint optimization framework that considers both communication and sensing performance,optimizing energy efficiency,detection probability,and the Cramér-Rao bound.The power allocation coefficients are derived through Nash equilibrium,while the precoding matrix is optimized using Sequential Convex Approximation(SCA)to address the non-convex nature of the optimization problem.Experimental results demonstrate that our proposed scheme significantly enhances the overall performance of the SAGIN-ISAC system.展开更多
Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink...Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink ISAC system that simultaneously serves multiple single-antenna communication users and senses multiple targets. Hybrid RIS differs from fully passive RIS in that it is composed of both active and passive elements, with the active elements having the effect of amplifying the signal in addition to phase-shifting. We maximize the achievable sum rate of communication users by collaboratively improving the beamforming matrix at the dual function base station(DFBS) and the phase-shifting matrix of the hybrid RIS, subject to the transmit power constraint at the DFBS, the signal-to-interference-plus-noise-ratio(SINR) constraint of the radar echo signal and the RIS constraint are satisfied at the same time. The builtin RIS-assisted ISAC design problem model is significantly non-convex due to the fractional objective function of this optimization problem and the coupling of the optimization variables in the objective function and constraints. As a result, we provide an effective alternating optimization approach based on fractional programming(FP) with block coordinate descent(BCD)to solve the optimization variables. Results from simulations show that the hybrid RIS-assisted ISAC system outperforms the other benchmark solutions.展开更多
This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive...This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive cellular infrastructure to create a vast and cooperative sensor network,enhancing environmental perception accuracy and coverage.On the other hand,sensing-assisted communication utilizes advanced sensing technologies to improve predictive beamforming and channel estimation performance in high-frequency and highmobility scenarios,thereby increasing communication efficiency and reliability.To validate our analysis,we present an example of channel knowledge map(CKM)-assisted beam tracking.This example demonstrates the practical advantages of incorporating CKM in enhancing beam tracking accuracy.Our analysis confirms that communication-assisted sensing may offer greater development potential due to its wide coverage and cost-effectiveness in large-scale applications.展开更多
A cooperative passive sensing framework for millimeter wave(mmWave)communication systems is proposed and demonstrated in a scenario with one mobile signal blocker.Specifically,in the uplink communication with at least...A cooperative passive sensing framework for millimeter wave(mmWave)communication systems is proposed and demonstrated in a scenario with one mobile signal blocker.Specifically,in the uplink communication with at least two transmitters,a cooperative detection method is proposed for the receiver to track the blocker’s trajectory,localize the transmitters and detect the potential link blockage jointly.To facilitate detection,the receiver collects the signal of each transmitter along a line-of-sight(LoS)path and a non-line-of-sight(NLoS)path separately via two narrow-beam phased arrays.The NLoS path involves scattering at the mobile blocker,allowing its identification through the Doppler frequency.By comparing the received signals of both paths,the Doppler frequency and angle-of-arrival(AoA)of the NLoS path can be estimated.To resolve the blocker’s trajectory and the transmitters’locations,the receiver should continuously track the mobile blocker to accumulate sufficient numbers of the Doppler frequency and AoA versus time observations.Finally,a gradient-descent-based algorithm is proposed for joint detection.With the reconstructed trajectory,the potential link blockage can be predicted.It is demonstrated that the system can achieve decimeterlevel localization and trajectory estimation,and predict the blockage time with an error of less than 0.1 s.展开更多
In unmanned aerial vehicle(UAV)networks,the high mobility of nodes leads to frequent changes in network topology,which brings challenges to the neighbor discovery(ND)for UAV networks.Integrated sensing and communicati...In unmanned aerial vehicle(UAV)networks,the high mobility of nodes leads to frequent changes in network topology,which brings challenges to the neighbor discovery(ND)for UAV networks.Integrated sensing and communication(ISAC),as an emerging technology in 6G mobile networks,has shown great potential in improving communication performance with the assistance of sensing information.ISAC obtains the prior information about node distribution,reducing the ND time.However,the prior information obtained through ISAC may be imperfect.Hence,an ND algorithm based on reinforcement learning is proposed.The learning automaton(LA)is applied to interact with the environment and continuously adjust the probability of selecting beams to accelerate the convergence speed of ND algorithms.Besides,an efficient ND algorithm in the neighbor maintenance phase is designed,which applies the Kalman filter to predict node movement.Simulation results show that the LA-based ND algorithm reduces the ND time by up to 32%compared with the Scan-Based Algorithm(SBA),which proves the efficiency of the proposed ND algorithms.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 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
Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localizati...Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localization.Compared to independent sensing and communication modules,dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains.When considering the communication core network,ISAC system facilitates multiple communication devices to collaborate for networked sensing.This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization.Specifically,we introduce a Time of Arrival(TOA)based multi-target localization scheme,which leverages the bi-static range measurements between the transmitter,target,and receiver channels in order to achieve elliptical localization.To obtain the low-complexity localization,a two-stage search-refine localization methodology is proposed.In the first stage,we propose a Successive Greedy Grid-Search(SGGS)algorithm and a Successive-Cancellation-List Grid-Search(SCLGS)algorithm to address the Measurement-to-Target Association(MTA)problem with relatively low computational complexity.In the second stage,a linear approximation refinement algorithm is derived to facilitate high-precision localization.Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.展开更多
Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,...Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,there exists performance trade-offbetween communication and sensing,in that they have competitions on the physical resources.Different resource allocation schemes will result in different sensing and communication performance,thus influencing the system’s overall performance.Therefore,how to model the system’s overall performance,and how to optimize it are key issues for ISAC.Relying on the large-scale deployment of the networks,cooperative ISAC has the advantages of wider coverage,more robust performance and good compatibility of multiple monostatic and multistatic sensing,compared to the non-cooperative ISAC.How to capture the performance gain of cooperation is a key issue for cooperative ISAC.To address the aforementioned vital problems,in this paper,we analyze the sensing accuracy gain,propose a unified ISAC performance evaluation framework and design several optimization methods in cooperative ISAC systems.The cooperative sensing accuracy gain is theoretically analyzed via Cramér Rao lower bound.The unified ISAC performance evaluation model is established by converting the communication mutual information to the effective minimum mean squared error.To optimize the unified ISAC performance,we design the optimization algorithms considering three factors:base stations’working modes,power allocation schemes and waveform design.Through simulations,we show the performance gain of the cooperative ISAC system and the effectiveness of the proposed optimization methods.展开更多
With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmi...With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmission and the computing requirements of intelligent tasks lead to the complex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the scenario of Io V.First,this paper proposes a system model with sensing,communication,and computing integration for multiple intelligent tasks with different requirements in the Io V.Secondly,joint resource allocation problems for real-time tasks and delay-tolerant tasks in the Io V are constructed respectively,including communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization problems,and the convergence and complexity of the algorithm are discussed.Finally,the experimental results based on real data sets verify the performance advantages of the proposed resource allocation scheme,compared to the existing ones.The exploration efficiency of our proposed DDQN-based algorithm is improved by at least about 5%,and our proposed resource allocation scheme improves the m AP performance by about 0.15 under resource constraints.展开更多
There is growing interest in the integrated sensing and communication(ISAC)to extend the 5G+/6G network capabilities by introducing sensing capability.While the solutions for mono-static or bi-static ISAC have shown f...There is growing interest in the integrated sensing and communication(ISAC)to extend the 5G+/6G network capabilities by introducing sensing capability.While the solutions for mono-static or bi-static ISAC have shown feasibility and benefits based on existing 5G physical layer design,whether and how to coordinate multiple ISAC devices to better exert networking performance are rarely discussed.3 rd Partnership Project(3GPP)has initiated the ISAC use cases study,and the follow-up studies for network architecture could be anticipated.In this article,we focus on gNB-based sensing mode and propose ISAC functional framework with given of highlevel service procedures to enable cellular based ISAC services.In the proposed ISAC framework,three types of network functions for sensing service as Sensing Function(SF),lightweight-Edge Sensing Function(ESF)and full-version-ESF are designed with interaction with network nodes to fulfill the latency requirements of ISAC use cases.Finally,with simulation evaluations and hardware testbed results,we further verify the performance benefit and feasibility to enable ISAC in 5G for the gNB-based sensing mode with new design on SF and related signaling protocols.展开更多
Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still fac...Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.展开更多
Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicl...Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicle(V2V)technology is difficult to break through the sensing blind area and ensure reliable sensing information.To overcome these problems,considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication(ISAC)technology.The mmWave base station(mmBS)transmits multiple beams consisting of communication beams and sensing beams.The sensing beams are responsible for sensing objects within the CAVs blind area,while the communication beams are responsible for transmitting the sensed information to the CAVs.To reduce the impact of inter-beam interference,a joint multiple beamwidth and power allocation(JMBPA)algorithm is proposed.By maximizing the communication transmission rate under the sensing constraints.The proposed non-convex optimization problem is transformed into a standard difference of two convex functions(D.C.)problem.Finally,the superiority of the lutions.The average transmission rate of communication beams remains over 3.4 Gbps,showcasing a significant improvement compared to other algorithms.Moreover,the satisfaction of sensing services remains steady.展开更多
In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JL...In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JLVE,which is challenging due to random fading,multipath interference,and complexly coupled system models,and thus the impact of channel fading and multipath interference on JLVE performance is not fully understood.To address this challenge,we exploit structured information models of the JLVE problem to render tractable performance quantification.Firstly,an individual closedform Cramer-Rao lower bound for vehicular localization,velocity detection and channel estimation,respectively,is established for gaining insights into performance limits of ICAS-based JLVE.Secondly,the impact of system resource factors and fading environments,e.g.,system bandwidth,the number of subcarriers,carrier frequency,antenna array size,transmission distance,spatial channel correlation,channel covariance,the number of interference paths and noise power,on the JLVE performance is theoretically analyzed.The associated closed-form JLVE performance analysis can not only provide theoretical foundations for ICAS receiver design but also provide a perfor mance benchmark for various JLVE methods。展开更多
Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high...Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance.展开更多
Reliable detection of weak phase signals under significant channel loss and complex noise environments is a crucial step for practical applications of optical integrated communication and sensing systems. In this lett...Reliable detection of weak phase signals under significant channel loss and complex noise environments is a crucial step for practical applications of optical integrated communication and sensing systems. In this letter, we propose and experimentally demonstrate an enhanced long-distance weak signal transmission method assisted by weak measurement. Performing heterodyne detection and light intensity compensation on two nearly symmetric post-selected paths, the method enables real-time estimation of a time-varying phase while maintaining robustness against technical noises proportional to light intensity or photon number, detector common-mode noise, and significant attenuation over long-distance transmission. Experimental results indicate a potential phase sensitivity at the level of 10-8rad even with a signal light intensity attenuation of 48.1 d B. Potentially, combining the adaptive adjustment strategy, the method may provide a viable solution in remote weak signal detection and extraction,thereby contributing to optical integrated communication and sensing.展开更多
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 by National Science and Technology Major Project of China(Project Number:2024ZD1300100)Fundamental Research Funds for the central universities(2024RC02)+1 种基金National Natural Science Foundation of China(62401077,62321001)Beijing Municipal Natural Science Foundation(L232003)。
文摘With the rapid growth of the low-altitude economy,the demand for typical low-altitude ap-plications has accelerated the advancement of inte-grated sensing and communications(ISAC)networks.This paper begins by analyzing representative ap-plication scenarios to clarify the core requirements of the low-altitude economy for modern ISAC net-works.By investigating the distinctive characteris-tics of ISAC networks in low-altitude environments,it presents a comprehensive analysis of key challenges and identifies four major issues:challenges in pre-cise target detection,interference management,in-consistent sensing and communication coverage,and the complexity of air-ground coordination and han-dover.Based on fundamental theories and principles,the paper proposes corresponding solutions,encom-passing advanced technologies for precise target de-tection and recognition,high-reliability networked de-tection,robust interference management,and seamless air-ground collaboration.These solutions aim to es-tablish a solid foundation for the future development of intelligent low-altitude networks and ensure effec-tive support for emerging applications.
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.
基金supported in part by the Natural Science Foundation of Chongqing under Grant CSTB2023NSCQ-LZX0118in part by the National Natural Science Foundation of China under Grant 62471052in part by the Beijing University of Posts and Telecommunications(BUPT)Excellent Ph.D.Students Foundation under Grant CX2023139.
文摘As key technologies in 6G,Space-Air-Ground Integrated Networks(SAGIN)promises to provide seamless global coverage through a comprehensive,ubiquitous communication system,while Integrated Sensing and Communications(ISAC)effectively addresses spectrum congestion by sharing spectrum resources and transceivers for simultaneous communication and sensing operations.However,existing ISAC research has primarily focused on terrestrial networks,with limited exploration of its applications in SAGIN environments.This paper proposes a novel SAGIN-ISAC scheme leveraging High-Altitude Platform Stations(HAPS).In this scheme,HAPS serves as a relay node that not only amplifies and forwards communication signals but also receives and processes target echo signals for parameter estimation.The satellite employs Resilient Massive Access(RMA)to provide communication services to different User Terminals(UTs).To address scenarios with an unknown number of targets,we develop a Two-threshold Detection and Parameter Multiple Signal Classification(MUSIC)algorithm(TDPM),which employs dual-threshold correlation detection to determine the number of targets and utilizes the MUSIC algorithm to estimate targets’Angle of Arrival(AoA),range,and relative velocity.Furthermore,we establish a joint optimization framework that considers both communication and sensing performance,optimizing energy efficiency,detection probability,and the Cramér-Rao bound.The power allocation coefficients are derived through Nash equilibrium,while the precoding matrix is optimized using Sequential Convex Approximation(SCA)to address the non-convex nature of the optimization problem.Experimental results demonstrate that our proposed scheme significantly enhances the overall performance of the SAGIN-ISAC system.
文摘Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink ISAC system that simultaneously serves multiple single-antenna communication users and senses multiple targets. Hybrid RIS differs from fully passive RIS in that it is composed of both active and passive elements, with the active elements having the effect of amplifying the signal in addition to phase-shifting. We maximize the achievable sum rate of communication users by collaboratively improving the beamforming matrix at the dual function base station(DFBS) and the phase-shifting matrix of the hybrid RIS, subject to the transmit power constraint at the DFBS, the signal-to-interference-plus-noise-ratio(SINR) constraint of the radar echo signal and the RIS constraint are satisfied at the same time. The builtin RIS-assisted ISAC design problem model is significantly non-convex due to the fractional objective function of this optimization problem and the coupling of the optimization variables in the objective function and constraints. As a result, we provide an effective alternating optimization approach based on fractional programming(FP) with block coordinate descent(BCD)to solve the optimization variables. Results from simulations show that the hybrid RIS-assisted ISAC system outperforms the other benchmark solutions.
文摘This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive cellular infrastructure to create a vast and cooperative sensor network,enhancing environmental perception accuracy and coverage.On the other hand,sensing-assisted communication utilizes advanced sensing technologies to improve predictive beamforming and channel estimation performance in high-frequency and highmobility scenarios,thereby increasing communication efficiency and reliability.To validate our analysis,we present an example of channel knowledge map(CKM)-assisted beam tracking.This example demonstrates the practical advantages of incorporating CKM in enhancing beam tracking accuracy.Our analysis confirms that communication-assisted sensing may offer greater development potential due to its wide coverage and cost-effectiveness in large-scale applications.
文摘A cooperative passive sensing framework for millimeter wave(mmWave)communication systems is proposed and demonstrated in a scenario with one mobile signal blocker.Specifically,in the uplink communication with at least two transmitters,a cooperative detection method is proposed for the receiver to track the blocker’s trajectory,localize the transmitters and detect the potential link blockage jointly.To facilitate detection,the receiver collects the signal of each transmitter along a line-of-sight(LoS)path and a non-line-of-sight(NLoS)path separately via two narrow-beam phased arrays.The NLoS path involves scattering at the mobile blocker,allowing its identification through the Doppler frequency.By comparing the received signals of both paths,the Doppler frequency and angle-of-arrival(AoA)of the NLoS path can be estimated.To resolve the blocker’s trajectory and the transmitters’locations,the receiver should continuously track the mobile blocker to accumulate sufficient numbers of the Doppler frequency and AoA versus time observations.Finally,a gradient-descent-based algorithm is proposed for joint detection.With the reconstructed trajectory,the potential link blockage can be predicted.It is demonstrated that the system can achieve decimeterlevel localization and trajectory estimation,and predict the blockage time with an error of less than 0.1 s.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant No.2024ZCJH01in part by the National Natural Science Foundation of China(NSFC)under Grant No.62271081in part by the National Key Research and Development Program of China under Grant No.2020YFA0711302.
文摘In unmanned aerial vehicle(UAV)networks,the high mobility of nodes leads to frequent changes in network topology,which brings challenges to the neighbor discovery(ND)for UAV networks.Integrated sensing and communication(ISAC),as an emerging technology in 6G mobile networks,has shown great potential in improving communication performance with the assistance of sensing information.ISAC obtains the prior information about node distribution,reducing the ND time.However,the prior information obtained through ISAC may be imperfect.Hence,an ND algorithm based on reinforcement learning is proposed.The learning automaton(LA)is applied to interact with the environment and continuously adjust the probability of selecting beams to accelerate the convergence speed of ND algorithms.Besides,an efficient ND algorithm in the neighbor maintenance phase is designed,which applies the Kalman filter to predict node movement.Simulation results show that the LA-based ND algorithm reduces the ND time by up to 32%compared with the Scan-Based Algorithm(SBA),which proves the efficiency of the proposed ND algorithms.
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 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Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localization.Compared to independent sensing and communication modules,dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains.When considering the communication core network,ISAC system facilitates multiple communication devices to collaborate for networked sensing.This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization.Specifically,we introduce a Time of Arrival(TOA)based multi-target localization scheme,which leverages the bi-static range measurements between the transmitter,target,and receiver channels in order to achieve elliptical localization.To obtain the low-complexity localization,a two-stage search-refine localization methodology is proposed.In the first stage,we propose a Successive Greedy Grid-Search(SGGS)algorithm and a Successive-Cancellation-List Grid-Search(SCLGS)algorithm to address the Measurement-to-Target Association(MTA)problem with relatively low computational complexity.In the second stage,a linear approximation refinement algorithm is derived to facilitate high-precision localization.Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.
文摘Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,there exists performance trade-offbetween communication and sensing,in that they have competitions on the physical resources.Different resource allocation schemes will result in different sensing and communication performance,thus influencing the system’s overall performance.Therefore,how to model the system’s overall performance,and how to optimize it are key issues for ISAC.Relying on the large-scale deployment of the networks,cooperative ISAC has the advantages of wider coverage,more robust performance and good compatibility of multiple monostatic and multistatic sensing,compared to the non-cooperative ISAC.How to capture the performance gain of cooperation is a key issue for cooperative ISAC.To address the aforementioned vital problems,in this paper,we analyze the sensing accuracy gain,propose a unified ISAC performance evaluation framework and design several optimization methods in cooperative ISAC systems.The cooperative sensing accuracy gain is theoretically analyzed via Cramér Rao lower bound.The unified ISAC performance evaluation model is established by converting the communication mutual information to the effective minimum mean squared error.To optimize the unified ISAC performance,we design the optimization algorithms considering three factors:base stations’working modes,power allocation schemes and waveform design.Through simulations,we show the performance gain of the cooperative ISAC system and the effectiveness of the proposed optimization methods.
基金supported by The Fundamental Research Funds for the Central Universities(No.2021XD-A01-1)The National Natural Science Foundation of China(No.92067202)。
文摘With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmission and the computing requirements of intelligent tasks lead to the complex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the scenario of Io V.First,this paper proposes a system model with sensing,communication,and computing integration for multiple intelligent tasks with different requirements in the Io V.Secondly,joint resource allocation problems for real-time tasks and delay-tolerant tasks in the Io V are constructed respectively,including communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization problems,and the convergence and complexity of the algorithm are discussed.Finally,the experimental results based on real data sets verify the performance advantages of the proposed resource allocation scheme,compared to the existing ones.The exploration efficiency of our proposed DDQN-based algorithm is improved by at least about 5%,and our proposed resource allocation scheme improves the m AP performance by about 0.15 under resource constraints.
文摘There is growing interest in the integrated sensing and communication(ISAC)to extend the 5G+/6G network capabilities by introducing sensing capability.While the solutions for mono-static or bi-static ISAC have shown feasibility and benefits based on existing 5G physical layer design,whether and how to coordinate multiple ISAC devices to better exert networking performance are rarely discussed.3 rd Partnership Project(3GPP)has initiated the ISAC use cases study,and the follow-up studies for network architecture could be anticipated.In this article,we focus on gNB-based sensing mode and propose ISAC functional framework with given of highlevel service procedures to enable cellular based ISAC services.In the proposed ISAC framework,three types of network functions for sensing service as Sensing Function(SF),lightweight-Edge Sensing Function(ESF)and full-version-ESF are designed with interaction with network nodes to fulfill the latency requirements of ISAC use cases.Finally,with simulation evaluations and hardware testbed results,we further verify the performance benefit and feasibility to enable ISAC in 5G for the gNB-based sensing mode with new design on SF and related signaling protocols.
基金the National Natural Science Foundation of China(No.62171462,No.62231027,No.U20B2038,No.61931011,No.62001514 and No.62271501).
文摘Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.
基金China Tele-com Research Institute Project(Grants No.HQBYG2200147GGN00)National Key R&D Program of China(2020YFB1807600)National Natural Science Foundation of China(NSFC)(Grant No.62022020).
文摘Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicle(V2V)technology is difficult to break through the sensing blind area and ensure reliable sensing information.To overcome these problems,considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication(ISAC)technology.The mmWave base station(mmBS)transmits multiple beams consisting of communication beams and sensing beams.The sensing beams are responsible for sensing objects within the CAVs blind area,while the communication beams are responsible for transmitting the sensed information to the CAVs.To reduce the impact of inter-beam interference,a joint multiple beamwidth and power allocation(JMBPA)algorithm is proposed.By maximizing the communication transmission rate under the sensing constraints.The proposed non-convex optimization problem is transformed into a standard difference of two convex functions(D.C.)problem.Finally,the superiority of the lutions.The average transmission rate of communication beams remains over 3.4 Gbps,showcasing a significant improvement compared to other algorithms.Moreover,the satisfaction of sensing services remains steady.
基金supported by the National Natural Science Foundation of China under 62001526by Natural Science Foundation of Guangdong Province under 2021A1515012021+2 种基金by National Key R&D Plan of China under Grant 2021YFB2900200partly by Major Talent Program of Guangdong Province under Grant 2021QN02X074by Fundamental Research Funds for the Central Universities, Sun Yat-sen University, under Grant 23QNPY22
文摘In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JLVE,which is challenging due to random fading,multipath interference,and complexly coupled system models,and thus the impact of channel fading and multipath interference on JLVE performance is not fully understood.To address this challenge,we exploit structured information models of the JLVE problem to render tractable performance quantification.Firstly,an individual closedform Cramer-Rao lower bound for vehicular localization,velocity detection and channel estimation,respectively,is established for gaining insights into performance limits of ICAS-based JLVE.Secondly,the impact of system resource factors and fading environments,e.g.,system bandwidth,the number of subcarriers,carrier frequency,antenna array size,transmission distance,spatial channel correlation,channel covariance,the number of interference paths and noise power,on the JLVE performance is theoretically analyzed.The associated closed-form JLVE performance analysis can not only provide theoretical foundations for ICAS receiver design but also provide a perfor mance benchmark for various JLVE methods。
基金supported by the Major Research Projects of the National Natural Science Foundation of China(92267202)the National Key Research and Development Project(2020YFA0711303)the BUPT Excellent Ph.D.Students Foundation(CX2022208).
文摘Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance.
基金supported by the National Natural Science Foundation of China(Grant No.62471289)the Natural Science Foundation of Shanghai (Grant No.24ZR1432900)+1 种基金the Innovation Program for Quantum Science and Technology (Grant No.2021ZD0300703)Shanghai Municipal Science and Technology Major Project (Grant No.2019SHZDZX01)。
文摘Reliable detection of weak phase signals under significant channel loss and complex noise environments is a crucial step for practical applications of optical integrated communication and sensing systems. In this letter, we propose and experimentally demonstrate an enhanced long-distance weak signal transmission method assisted by weak measurement. Performing heterodyne detection and light intensity compensation on two nearly symmetric post-selected paths, the method enables real-time estimation of a time-varying phase while maintaining robustness against technical noises proportional to light intensity or photon number, detector common-mode noise, and significant attenuation over long-distance transmission. Experimental results indicate a potential phase sensitivity at the level of 10-8rad even with a signal light intensity attenuation of 48.1 d B. Potentially, combining the adaptive adjustment strategy, the method may provide a viable solution in remote weak signal detection and extraction,thereby contributing to optical integrated communication and sensing.
