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
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
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
In this paper,we propose a rate splitting multiple access(RSMA)based integrated sensing and communication system(ISAC),where the sensing and communication are realized simultaneously with the RSMA signal.Further,recon...In this paper,we propose a rate splitting multiple access(RSMA)based integrated sensing and communication system(ISAC),where the sensing and communication are realized simultaneously with the RSMA signal.Further,reconfigurable holographic surface(RHS)is utilized to replace the traditional antennas for beam generation,expecting to combine the advantages of RSMA and RHS.To maximize the weighted summation of system rate and probing power,an optimization problem is formulated to jointly design the digital beamformer,the holographic beamformer and the message splitting vectors.To solve the non-convex problem,we first decompose it into two subproblems,where one jointly designs the digital beamformer and message splitting vectors,and the other deals with the holographic beamformer.An iterative algorithm,which leverages successive convex approximation and semi-definite relaxation,is proposed to achieve the sub-optimal solution through solving these two subproblems alternatively.Simulations confirm the effectiveness and efficiency of the proposed algorithm.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
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
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
With the rapid advancements in edge computing and artificial intelligence,federated learning(FL)has gained momentum as a promising approach to collaborative data utilization across organizations and devices,while ensu...With the rapid advancements in edge computing and artificial intelligence,federated learning(FL)has gained momentum as a promising approach to collaborative data utilization across organizations and devices,while ensuring data privacy and information security.In order to further harness the energy efficiency of wireless networks,an integrated sensing,communication and computation(ISCC)framework has been proposed,which is anticipated to be a key enabler in the era of 6G networks.Although the advantages of pushing intelligence to edge devices are multi-fold,some challenges arise when incorporating FL into wireless networks under the umbrella of ISCC.This paper provides a comprehensive survey of FL,with special emphasis on the design and optimization of ISCC.We commence by introducing the background and fundamentals of FL and the ISCC framework.Subsequently,the aforementioned challenges are highlighted and the state of the art in potential solutions is reviewed.Finally,design guidelines are provided for the incorporation of FL and ISCC.Overall,this paper aims to contribute to the understanding of FL in the context of wireless networks,with a focus on the ISCC framework,and provide insights into addressing the challenges and optimizing the design for the integration of FL into future 6G networks.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
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
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ...Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.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
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
Visible light communication plays an essential role in the next-generation 6G network due to its extremely high bandwidth and ultrafast transmission speed.Incorporating position sensing functionality into the communic...Visible light communication plays an essential role in the next-generation 6G network due to its extremely high bandwidth and ultrafast transmission speed.Incorporating position sensing functionality into the communication system is highly desired for achieving target-oriented beamforming and accommodating high-speed data service.However,an efficient solution to integrated sensing and light communication remains challenging.Here,we demonstrate an integrated system that concurrently accomplishes high-precision sensing and high-speed data transmission by spatio-temporal modulation of the illumination and computational reconstruction.We developed a compressive angular projection imaging scheme to achieve rapid three-dimensional localization with high resolution,and a jointly optimized waveform design ensures slight sacrifice in the transmission data rate on the integrated system.We experimentally demonstrated a resolving resolution of 1 mm in lateral and 4 cm in depth within 0.6 m×0.6 m×0.6 m volume over 2 m distance at the sensing speed of 39 Hz in both static and dynamic conditions.This capability enables adaptive beamforming,which significantly enhances the data rate by 184%to permit errorless transmission of high-throughput virtual reality videos.Our work offers a promising route for intelligent wireless light communication systems with spatial perception capability,presenting the possibility of cable-free,immersive virtual reality experiences.展开更多
The scientific monitoring and reliable telecommunications(SMART)initiative,led by a joint task force including ITU,aims to integrate electronic sensors into undersea telecommunications cables for real-time and high-se...The scientific monitoring and reliable telecommunications(SMART)initiative,led by a joint task force including ITU,aims to integrate electronic sensors into undersea telecommunications cables for real-time and high-sensitivity subsea monitoring.The current integrated sensing and communication(ISAC)solution to the SMART application still relies on wavelength band multiplexing of sensing information via Ethernet switches,leading to optical communication bandwidth waste.To achieve the dense and low-interference ISAC for SMART network applications,we demonstrate the co-transmissions of coherent optical digital subcarrier modulation(DSCM)communication signals and temperature sensing information in the SMART system.Besides the co-transmission capability,the special design of the sensing transmission format is made to enable the compatible DSP with DSCM communications,which shares the same wavelength channel.Moreover,due to the different physical locations of the in-line sensing joints to the communication transceivers in the SMART system,it is hard to align the wavelength of the communication laser and the sensing one,which cannot ensure the precise allocation of sensing information into the frequency blanks of DSCM communication signals.To deal with these two issues,the sensing information at inline joints is proposed to be modulated in the manner of optical single-sideband(SSB)modulation and frequency modulation(FM),and then the precise allocation into the frequency blanks of DSCM communication signals can be realized,along with the full compatibility to demodulate the sensed temperature using the traditional frequency offset estimation in coherent DSP.Experiments on a two-span repeatered single-mode fiber link validate the integration of 20 GBaud optical DP-QAM16 transmissions and real-time temperature sensing at a sensing joint.Advanced communications are enabled by implementing space-time coding on DSCM communication signals,with 0.2 dB Q factor improvement.As for the sensing functionality,the temperature sensing resolution at 0.0625°C,which reaches the limitation of the employed electronic thermometer DS18B20,has been obtained by using the communication-compatible DSP.We believe the proposed ISAC scheme along with the corresponding DSP flowchart makes sense for monitoring the subsea via the advanced SMART cables.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
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
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
In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users t...In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming.Specifically,the weighted minimum mean-square error method is first used to reformulate the original problem into an equivalent one.Then,we utilize an alternating optimization algorithm to decouple the optimization variables and decompose this challenging problem into two subproblems.Given reflecting coefficients,a penalty-based algorithm is utilized to deal with the non-convex radar Signal-to-Noise Ratio(SNR)constraints.For the given beamforming matrix of the base station,we apply majorization-minimization to transform the problem into a Quadratic Constraint Quadratic Programming(QCQP)problem,which is ultimately solved using a Semi-Definite Relaxation(SDR)based algorithm.Simulation results illustrate the advantage of deploying reconfigurable intelligent surface in the considered multi-user MultipleInput Multiple-Output(MIMO)ISAC systems.展开更多
Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming ...Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming upload traffic may lead to unacceptable uploading time.To tackle this issue,for tasks taking environmental data as input,the data perceived by roadside units(RSU)equipped with several sensors can be directly exploited for computation,resulting in a novel task offloading paradigm with integrated communications,sensing and computing(I-CSC).With this paradigm,vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading.By optimizing the computation mode and network resources,in this paper,we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task.Although this nonconvex problem can be handled by the alternating minimization(AM)algorithm that alternatively minimizes the divided four sub-problems,it leads to high computational complexity and local optimal solution.To tackle this challenge,we propose a creative structural knowledge-driven meta-learning(SKDML)method,involving both the model-based AM algorithm and neural networks.Specifically,borrowing the iterative structure of the AM algorithm,also referred to as structural knowledge,the proposed SKDML adopts long short-term memory(LSTM)networkbased meta-learning to learn an adaptive optimizer for updating variables in each sub-problem,instead of the handcrafted counterpart in the AM algorithm.Furthermore,to pull out the solution from the local optimum,our proposed SKDML updates parameters in LSTM with the global loss function.Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.展开更多
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.
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 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 by the Joint Funds of the National Natural Science Foundation of China(No.U23A20277)the Joint Funds of the National Natural Science Foundation of China(No.U22A2003).
文摘In this paper,we propose a rate splitting multiple access(RSMA)based integrated sensing and communication system(ISAC),where the sensing and communication are realized simultaneously with the RSMA signal.Further,reconfigurable holographic surface(RHS)is utilized to replace the traditional antennas for beam generation,expecting to combine the advantages of RSMA and RHS.To maximize the weighted summation of system rate and probing power,an optimization problem is formulated to jointly design the digital beamformer,the holographic beamformer and the message splitting vectors.To solve the non-convex problem,we first decompose it into two subproblems,where one jointly designs the digital beamformer and message splitting vectors,and the other deals with the holographic beamformer.An iterative algorithm,which leverages successive convex approximation and semi-definite relaxation,is proposed to achieve the sub-optimal solution through solving these two subproblems alternatively.Simulations confirm the effectiveness and efficiency of the proposed algorithm.
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.
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.
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.
文摘With the rapid advancements in edge computing and artificial intelligence,federated learning(FL)has gained momentum as a promising approach to collaborative data utilization across organizations and devices,while ensuring data privacy and information security.In order to further harness the energy efficiency of wireless networks,an integrated sensing,communication and computation(ISCC)framework has been proposed,which is anticipated to be a key enabler in the era of 6G networks.Although the advantages of pushing intelligence to edge devices are multi-fold,some challenges arise when incorporating FL into wireless networks under the umbrella of ISCC.This paper provides a comprehensive survey of FL,with special emphasis on the design and optimization of ISCC.We commence by introducing the background and fundamentals of FL and the ISCC framework.Subsequently,the aforementioned challenges are highlighted and the state of the art in potential solutions is reviewed.Finally,design guidelines are provided for the incorporation of FL and ISCC.Overall,this paper aims to contribute to the understanding of FL in the context of wireless networks,with a focus on the ISCC framework,and provide insights into addressing the challenges and optimizing the design for the integration of FL into future 6G networks.
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National Natural Science Foundation of China under Grant 62571248 and Grant 62201266Key Laboratory of Intelligent Space TTC&O(Space Engineering University),Ministry of Education under Grant CYK2025-01-12。
文摘Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.
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National Key Research and Development Program of China(2023YFB2804701)National Natural Science Foundation of China(62401156,61925104,62201157,62231018)。
文摘Visible light communication plays an essential role in the next-generation 6G network due to its extremely high bandwidth and ultrafast transmission speed.Incorporating position sensing functionality into the communication system is highly desired for achieving target-oriented beamforming and accommodating high-speed data service.However,an efficient solution to integrated sensing and light communication remains challenging.Here,we demonstrate an integrated system that concurrently accomplishes high-precision sensing and high-speed data transmission by spatio-temporal modulation of the illumination and computational reconstruction.We developed a compressive angular projection imaging scheme to achieve rapid three-dimensional localization with high resolution,and a jointly optimized waveform design ensures slight sacrifice in the transmission data rate on the integrated system.We experimentally demonstrated a resolving resolution of 1 mm in lateral and 4 cm in depth within 0.6 m×0.6 m×0.6 m volume over 2 m distance at the sensing speed of 39 Hz in both static and dynamic conditions.This capability enables adaptive beamforming,which significantly enhances the data rate by 184%to permit errorless transmission of high-throughput virtual reality videos.Our work offers a promising route for intelligent wireless light communication systems with spatial perception capability,presenting the possibility of cable-free,immersive virtual reality experiences.
基金National Natural Science Foundation of China(62475178)Yangtze River Delta Region Integration Project(2024CSJGG2600).
文摘The scientific monitoring and reliable telecommunications(SMART)initiative,led by a joint task force including ITU,aims to integrate electronic sensors into undersea telecommunications cables for real-time and high-sensitivity subsea monitoring.The current integrated sensing and communication(ISAC)solution to the SMART application still relies on wavelength band multiplexing of sensing information via Ethernet switches,leading to optical communication bandwidth waste.To achieve the dense and low-interference ISAC for SMART network applications,we demonstrate the co-transmissions of coherent optical digital subcarrier modulation(DSCM)communication signals and temperature sensing information in the SMART system.Besides the co-transmission capability,the special design of the sensing transmission format is made to enable the compatible DSP with DSCM communications,which shares the same wavelength channel.Moreover,due to the different physical locations of the in-line sensing joints to the communication transceivers in the SMART system,it is hard to align the wavelength of the communication laser and the sensing one,which cannot ensure the precise allocation of sensing information into the frequency blanks of DSCM communication signals.To deal with these two issues,the sensing information at inline joints is proposed to be modulated in the manner of optical single-sideband(SSB)modulation and frequency modulation(FM),and then the precise allocation into the frequency blanks of DSCM communication signals can be realized,along with the full compatibility to demodulate the sensed temperature using the traditional frequency offset estimation in coherent DSP.Experiments on a two-span repeatered single-mode fiber link validate the integration of 20 GBaud optical DP-QAM16 transmissions and real-time temperature sensing at a sensing joint.Advanced communications are enabled by implementing space-time coding on DSCM communication signals,with 0.2 dB Q factor improvement.As for the sensing functionality,the temperature sensing resolution at 0.0625°C,which reaches the limitation of the employed electronic thermometer DS18B20,has been obtained by using the communication-compatible DSP.We believe the proposed ISAC scheme along with the corresponding DSP flowchart makes sense for monitoring the subsea via the advanced SMART cables.
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 under Grants 62201137 and 62331023in part by the Fundamental Research Funds for the Central Universities under Grant 2242022k60001in part by the Fundamental Research Funds for the Central Universities under Grant 2242025K20001。
文摘In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming.Specifically,the weighted minimum mean-square error method is first used to reformulate the original problem into an equivalent one.Then,we utilize an alternating optimization algorithm to decouple the optimization variables and decompose this challenging problem into two subproblems.Given reflecting coefficients,a penalty-based algorithm is utilized to deal with the non-convex radar Signal-to-Noise Ratio(SNR)constraints.For the given beamforming matrix of the base station,we apply majorization-minimization to transform the problem into a Quadratic Constraint Quadratic Programming(QCQP)problem,which is ultimately solved using a Semi-Definite Relaxation(SDR)based algorithm.Simulation results illustrate the advantage of deploying reconfigurable intelligent surface in the considered multi-user MultipleInput Multiple-Output(MIMO)ISAC systems.
基金supported in part by National Key Research and Development Program of China(2020YFB1807700)in part by National Natural Science Foundation of China(62201414)+2 种基金in part by Qinchuangyuan Project(OCYRCXM-2022-362)in part by Science and Technology Project of Guangzhou(2023A04J1741)in part by Chongqing key laboratory of Mobile Communications Technologg(cqupt-mct-202202).
文摘Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming upload traffic may lead to unacceptable uploading time.To tackle this issue,for tasks taking environmental data as input,the data perceived by roadside units(RSU)equipped with several sensors can be directly exploited for computation,resulting in a novel task offloading paradigm with integrated communications,sensing and computing(I-CSC).With this paradigm,vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading.By optimizing the computation mode and network resources,in this paper,we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task.Although this nonconvex problem can be handled by the alternating minimization(AM)algorithm that alternatively minimizes the divided four sub-problems,it leads to high computational complexity and local optimal solution.To tackle this challenge,we propose a creative structural knowledge-driven meta-learning(SKDML)method,involving both the model-based AM algorithm and neural networks.Specifically,borrowing the iterative structure of the AM algorithm,also referred to as structural knowledge,the proposed SKDML adopts long short-term memory(LSTM)networkbased meta-learning to learn an adaptive optimizer for updating variables in each sub-problem,instead of the handcrafted counterpart in the AM algorithm.Furthermore,to pull out the solution from the local optimum,our proposed SKDML updates parameters in LSTM with the global loss function.Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.
