To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference a...To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.展开更多
With the rapid development of information technology,IoT devices play a huge role in physiological health data detection.The exponential growth of medical data requires us to reasonably allocate storage space for clou...With the rapid development of information technology,IoT devices play a huge role in physiological health data detection.The exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge nodes.The storage capacity of edge nodes close to users is limited.We should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging problem.Our paper proposes a redundant data detection method that meets the privacy protection requirements.By scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot data.It has the same effect as zero-knowledge proof,and it will not reveal the privacy of users.In addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the data.We use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is deleted.The feasibility of the scheme is proved through safety analysis and efficiency analysis.展开更多
Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content deliver...Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.展开更多
Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit(LEO).However,these constellations often rely on be...Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit(LEO).However,these constellations often rely on bent-pipe architecture,resulting in high communication costs.Existing onboard inference architectures suffer from limitations in terms of low accuracy and inflexibility in the deployment and management of in-orbit applications.To address these challenges,we propose a cloud-native-based satellite design specifically tailored for Earth Observation tasks,enabling diverse computing paradigms.In this work,we present a case study of a satellite-ground collaborative inference system deployed in the Tiansuan constellation,demonstrating a remarkable 50%accuracy improvement and a substantial 90%data reduction.Our work sheds light on in-orbit energy,where in-orbit computing accounts for 17%of the total onboard energy consumption.Our approach represents a significant advancement of cloud-native satellite,aiming to enhance the accuracy of in-orbit computing while simultaneously reducing communication cost.展开更多
This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to...This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).展开更多
In the field of speech bandwidth exten-sion,it is difficult to achieve high speech quality based on the shallow statistical model method.Although the application of deep learning has greatly improved the extended spee...In the field of speech bandwidth exten-sion,it is difficult to achieve high speech quality based on the shallow statistical model method.Although the application of deep learning has greatly improved the extended speech quality,the high model complex-ity makes it infeasible to run on the client.In order to tackle these issues,this paper proposes an end-to-end speech bandwidth extension method based on a temporal convolutional neural network,which greatly reduces the complexity of the model.In addition,a new time-frequency loss function is designed to en-able narrowband speech to acquire a more accurate wideband mapping in the time domain and the fre-quency domain.The experimental results show that the reconstructed wideband speech generated by the proposed method is superior to the traditional heuris-tic rule based approaches and the conventional neu-ral network methods for both subjective and objective evaluation.展开更多
Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its ...Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.展开更多
With the continuous development of wireless communication technology,the number of access devices continues to soar,which poses a grate challenge to the already scarce spectrum resources.Meanwhile,6G will be an era of...With the continuous development of wireless communication technology,the number of access devices continues to soar,which poses a grate challenge to the already scarce spectrum resources.Meanwhile,6G will be an era of air-space-terrestrial-sea integration,and satellite spectrum resources are also very tight in the context of giant constellations.In this paper,we propose a Non-Orthogonal Multiple Access(NOMA)based spectrum sensing scheme for the future satellite-terrestrial communication scenarios,and design the transceiver from uplink and downlink scenarios,respectively.In order to better identify the user's transmission status,we obtain the feature values of each user through feature detection to make decision.We combine these two technologies to design the transceiver architecture and deduce the threshold value of feature detection in the satellite-terrestrial communication scenario.Simulations are performed in each scenario,and the results illustrate that the proposed scheme combining NOMA and spectrum sensing can greatly improve the throughput with a similar detection probability as Orthogonal Multiple Access(OMA).展开更多
The Global Navigation Satellite System(GNSS)has been widely used in various fields.To achieve positioning,the receiver must first lock the satellite signal.This is a complicated and expensive process that consumes a l...The Global Navigation Satellite System(GNSS)has been widely used in various fields.To achieve positioning,the receiver must first lock the satellite signal.This is a complicated and expensive process that consumes a lot of resources of the receiver.For this reason,this paper proposes a new fast acquisition algorithm with High Signal-tonoise ratio(SNR)performance based on sparse fast Fourier transform(HSFFT).The algorithm first replaces the IFFT process of the traditional parallel code phase capture algorithm with inverse sparse fast Fourier transform(ISFFT)with better computing performance,and then uses linear search combined with code phase discrimination to replace the positioning loop and the estimation loop with poor noise immunity in ISFFT.Theoretical analysis and simulation results show that,compared with the existing SFFT parallel code phase capture algorithm,the calculation amount of this algorithm is reduced by 19%,and the SNR performance is improved by about 5dB.Compared with the classic FFT parallel code phase capture algorithm,the calculation amount of the algorithm in this paper is reduced by 43%,and when the capture probability is greater than 95%,the SNR performance of the two is approximately the same.展开更多
The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications.On the technical line,the cross-modal AI generation application based on human feedback s...The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications.On the technical line,the cross-modal AI generation application based on human feedback system is accelerated.In the business model,the scenes to realize interactive functions are constantly enriched.This paper reviews the evolution process of AIGC,closely follows the current situation of the coexistence of business acceleration and technical worries in the application of artificial intelligence education,analyzes the application of AIGC education in 7 subdivided fields,and analyzes the optimization direction of application cases from the perspective of perception-cognition-creation technology maturity matrix.The 3 recommendations and 2 follow-up research directions will promote the scientific application of artificial intelligence education in the AIGC period.展开更多
Federated edge learning(FEEL)technology for vehicular networks is considered as a promising technology to reduce the computation workload while keeping the privacy of users.In the FEEL system,vehicles upload data to t...Federated edge learning(FEEL)technology for vehicular networks is considered as a promising technology to reduce the computation workload while keeping the privacy of users.In the FEEL system,vehicles upload data to the edge servers,which train the vehicles’data to update local models and then return the result to vehicles to avoid sharing the original data.However,the cache queue in the edge is limited and the channel between edge server and each vehicle is time-varying.Thus,it is challenging to select a suitable number of vehicles to ensure that the uploaded data can keep a stable cache queue in edge server while maximizing the learning accuracy.Moreover,selecting vehicles with different resource statuses to update data will affect the total amount of data involved in training,which further affects the model accuracy.In this paper,we propose a vehicle selection scheme,which maximizes the learning accuracy while ensuring the stability of the cache queue,where the statuses of all the vehicles in the coverage of edge server are taken into account.The performance of this scheme is evaluated through simulation experiments,which indicates that our proposed scheme can perform better than the known benchmark scheme.展开更多
As the emergence of various highbandwidth services and the requirements to support 5G/Wi-Fi 6 wireless networks,the next generation fixed networks,i.e.F5G,are expected to be realized in the 5G era.F5G is endowed with ...As the emergence of various highbandwidth services and the requirements to support 5G/Wi-Fi 6 wireless networks,the next generation fixed networks,i.e.F5G,are expected to be realized in the 5G era.F5G is endowed with new characteristics,including ultra-high bandwidth,all-optical connections and optimal service experience.With the prospect of optical-to-everywhere,optical technologies are used for mobile front-haul,mid-haul,and back-haul.Optical access networks would play an important role in F5G to support radio access network and fixed access network.Low-latency PON is a key for cost effective-haul traffic aggregation.In terms of signal transmission,intensity modulation directdetection(IM-DD)is a promising scheme due to its simple architecture.The fundamental challenge associated with direct-detection is the disappearance of the transmitted signal’s phase.In access network,the flexibility and low latency are the two key factors affecting service experience.In this article,we review the evolution of PONs and the challenges of current PONs in detail.We analyze key enabling digital signal processing(DSP)techniques,including detection linearization for direct-detection and simplified coherent detection,adaptive equalizers,digital filer enabled flexible access network and low-latency inter-ONU communications.Finally,we discuss the developing trends of future optical access networks.展开更多
This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We...This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We aim to maximize the throughput overall GTs by jointly optimizing the UAVs’trajectory,the GTs’scheduling and power allocation.Unlike most prior studies,we consider the UAVs’turning and climbing angle constraints,the UAVs’three-dimensional(3D)trajectory constraints,minimum UAV-to-UAV(U2U)distance constraint,and the GTs’transmit power requirements.However,the formulated problem is a mixed-integer non-convex problem and is intractable to work it out with conventional optimization methods.To tackle this difficulty,we propose an efficient robust iterative algorithm to decompose the original problem be three sub-problems and acquire the suboptimal solution via utilizing the block coordinate descent(BCD)method,successive convex approximation(SCA)technique,and S-procedure.Extensive simulation results show that our proposed robust iterative algorithm offers a substantial gain in the system performance compared with the benchmark algorithms.展开更多
Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks,but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated.To this e...Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks,but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated.To this end,this article discusses the concepts of edge intelligence from the semantic cognitive perspective.Two instructive theoretical models for edge semantic cognitive intelligence(ESCI)are first established.Afterwards,the ESCI framework orchestrating deep learning with semantic communication is discussed.Two representative applications are present to shed light on the prospect of ESCI in 6G networks.Some open problems are finally listed to elicit the future research directions of ESCI.展开更多
In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the sep...In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the separated optimization paradigm.In this context,this paper provides a comprehensive tutorial that overview how joint source-channel coding(JSCC)can be employed for improving overall system performance.For the purpose,we first introduce the communication requirements and performance metrics for 6G.Then,we provide an overview of the source-channel separation theorem and why it may not hold in practical applications.In addition,we focus on two new JSCC schemes called the double low-density parity-check(LDPC)codes and the double polar codes,respectively,giving their detailed coding and decoding processes and corresponding performance simulations.In a nutshell,this paper constitutes a tutorial on the JSCC scheme tailored to the needs of future 6G communications.展开更多
In terahertz communication,the direct frequency conversion structure in which orthogonal mixer is the main frequency conversion unit,makes engineers get into trouble of in-phase(I)branch and quadrature(Q)branch imbala...In terahertz communication,the direct frequency conversion structure in which orthogonal mixer is the main frequency conversion unit,makes engineers get into trouble of in-phase(I)branch and quadrature(Q)branch imbalance,carrier wave leakage,etc.These damages result in system performance tremendous degrades.We proposed a semiblind method to estimate the I/Q imbalance of THz orthogonal modulator,based on predefined preamble and pilot symbols for quadrature amplitude modulation(QAM).In this paper,a transmitter with Y band quadrature mixer and 20Gbps base-band signal has been tested.The bandwidth of the baseband signal was 7GHz,and the modulation type was 16QAM.By this method,7dB improvement of the system’s symbol Mean Square Error(MSE)has been got.That means the proposed method can be used to eliminate the I/Q imbalance effectively.展开更多
Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite net...Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme.展开更多
Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliabil...Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliability and efficiency of data sharing need to be further enhanced.Federated learning allows the server to exchange parameters without obtaining private data from clients so that the privacy is protected.Broad learning system is a novel artificial intelligence technology that can improve training efficiency of data set.Thus,we propose a federated bidirectional connection broad learning scheme(FeBBLS)to solve the data sharing issues.Firstly,we adopt the bidirectional connection broad learning system(BiBLS)model to train data set in vehicular nodes.The server aggregates the collected parameters of BiBLS from vehicular nodes through the federated broad learning system(FedBLS)algorithm.Moreover,we propose a clustering FedBLS algorithm to offload the data sharing into clusters for improving the aggregation capability of the model.Some simulation results show our scheme can improve the efficiency and prediction accuracy of data sharing and protect the privacy of data sharing.展开更多
The terahertz(THz)antennas,which have features of small size,wide frequency bandwidth and high data rate,are important devices for transmitting and receiving THz electromagnetic waves in the emerging THz systems.Howev...The terahertz(THz)antennas,which have features of small size,wide frequency bandwidth and high data rate,are important devices for transmitting and receiving THz electromagnetic waves in the emerging THz systems.However,most of THz antennas suffer from relatively high loss and low fabrication precision due to their small sizes in high frequency bands of THz waves.Therefore,this paper presents a detailed overview of the most recent research on the performance improvement of THz antennas.Firstly,the development of THz antennas is briefly reviewed and the basic design ideas of THz antennas are introduced.Then,THz antennas are categorized as metallic antennas,dielectric antennas and new material antennas.After that,the latest research progress in THz photoconductive antennas,THz horn antennas,THz lens antennas,THz microstrip antennas and THz on-chip antennas are discussed.In particular,the practical difficulties for the development of THz antennas are discussed with promising approaches.In addition,this paper also presents a short review of the process technology of THz antennas.Finally,the vital challenges and the future research directions for THz antennas are presented.展开更多
In this paper, we investigate a joint beamforming and time switching(TS) design for an energy-constrained cognitive two-way relay(TWR) network. In the network, the energy-constrained secondary user(SU) relay employs T...In this paper, we investigate a joint beamforming and time switching(TS) design for an energy-constrained cognitive two-way relay(TWR) network. In the network, the energy-constrained secondary user(SU) relay employs TS protocol to harvest energy from the signals sent by the circuit-powered primary user(PU) transmitter, and then exploits the harvested energy to perform information forwarding. Our aim is to maximize the sum rate of SUs under the constraints of the data rate of PU, the energy harvesting and the transmit power of the SU relay. To determine the beamforming matrix and TS ratio, we decouple the original non-convex problem into two subproblems which can be solved by semidefinite relaxation and successive convex optimization methods. Furthermore, we derive closed form expressions of the optimal solutions for each subproblem, which facilitates the design of a suboptimal iterative algorithm to handle the original sum rate maximization problem. Simulation results are presented to illustrate the effectiveness and superior performance of the proposed joint design against other conventional schemes in the literature.展开更多
基金supported in part by the National Natural Science Foundation of China (No.62271253,61901523,62001381)Fundamental Research Funds for the Central Universities (No.NS2023018)+2 种基金the National Aerospace Science Foundation of China under Grant 2023Z021052002the open research fund of National Mobile Communications Research Laboratory,Southeast University (No.2023D09)Postgraduate Research & Practice Innovation Program of NUAA (No.xcxjh20220402)。
文摘To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.
基金sponsored by the National Natural Science Foundation of China under grant number No. 62172353, No. 62302114, No. U20B2046 and No. 62172115Innovation Fund Program of the Engineering Research Center for Integration and Application of Digital Learning Technology of Ministry of Education No.1331007 and No. 1311022+1 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions Grant No. 17KJB520044Six Talent Peaks Project in Jiangsu Province No.XYDXX-108
文摘With the rapid development of information technology,IoT devices play a huge role in physiological health data detection.The exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge nodes.The storage capacity of edge nodes close to users is limited.We should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging problem.Our paper proposes a redundant data detection method that meets the privacy protection requirements.By scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot data.It has the same effect as zero-knowledge proof,and it will not reveal the privacy of users.In addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the data.We use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is deleted.The feasibility of the scheme is proved through safety analysis and efficiency analysis.
基金supported by National Natural Sciences Foundation of China(No.62271165,62027802,61831008)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030297,2021A1515011572)Shenzhen Science and Technology Program ZDSYS20210623091808025,Stable Support Plan Program GXWD20231129102638002.
文摘Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.
基金supported by National Natural Science Foundation of China(62032003).
文摘Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit(LEO).However,these constellations often rely on bent-pipe architecture,resulting in high communication costs.Existing onboard inference architectures suffer from limitations in terms of low accuracy and inflexibility in the deployment and management of in-orbit applications.To address these challenges,we propose a cloud-native-based satellite design specifically tailored for Earth Observation tasks,enabling diverse computing paradigms.In this work,we present a case study of a satellite-ground collaborative inference system deployed in the Tiansuan constellation,demonstrating a remarkable 50%accuracy improvement and a substantial 90%data reduction.Our work sheds light on in-orbit energy,where in-orbit computing accounts for 17%of the total onboard energy consumption.Our approach represents a significant advancement of cloud-native satellite,aiming to enhance the accuracy of in-orbit computing while simultaneously reducing communication cost.
基金supported by Beijing Natural Science Foundation (L202003)。
文摘This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).
文摘In the field of speech bandwidth exten-sion,it is difficult to achieve high speech quality based on the shallow statistical model method.Although the application of deep learning has greatly improved the extended speech quality,the high model complex-ity makes it infeasible to run on the client.In order to tackle these issues,this paper proposes an end-to-end speech bandwidth extension method based on a temporal convolutional neural network,which greatly reduces the complexity of the model.In addition,a new time-frequency loss function is designed to en-able narrowband speech to acquire a more accurate wideband mapping in the time domain and the fre-quency domain.The experimental results show that the reconstructed wideband speech generated by the proposed method is superior to the traditional heuris-tic rule based approaches and the conventional neu-ral network methods for both subjective and objective evaluation.
基金supported in part by the National Science Foundation Project of P.R.China (No.61931001)the Fundamental Research Funds for the Central Universities under Grant (No.FRFAT-19-010)the Scientific and Technological Innovation Foundation of Foshan,USTB (No.BK20AF003)。
文摘Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.
基金supported in part by the National Key Research and Development Program of China(2018YFB1802300)the Science and Technology Commission Foundation of Shanghai(Nos.21511101400 and 22511100600)+2 种基金the Young Elite Scientists Sponsorship Program by CICthe Program of Shanghai Academic/Technology Research Leader(No.21XD1433700)the Shanghai Rising-Star Program(No.21QC1400800)。
文摘With the continuous development of wireless communication technology,the number of access devices continues to soar,which poses a grate challenge to the already scarce spectrum resources.Meanwhile,6G will be an era of air-space-terrestrial-sea integration,and satellite spectrum resources are also very tight in the context of giant constellations.In this paper,we propose a Non-Orthogonal Multiple Access(NOMA)based spectrum sensing scheme for the future satellite-terrestrial communication scenarios,and design the transceiver from uplink and downlink scenarios,respectively.In order to better identify the user's transmission status,we obtain the feature values of each user through feature detection to make decision.We combine these two technologies to design the transceiver architecture and deduce the threshold value of feature detection in the satellite-terrestrial communication scenario.Simulations are performed in each scenario,and the results illustrate that the proposed scheme combining NOMA and spectrum sensing can greatly improve the throughput with a similar detection probability as Orthogonal Multiple Access(OMA).
文摘The Global Navigation Satellite System(GNSS)has been widely used in various fields.To achieve positioning,the receiver must first lock the satellite signal.This is a complicated and expensive process that consumes a lot of resources of the receiver.For this reason,this paper proposes a new fast acquisition algorithm with High Signal-tonoise ratio(SNR)performance based on sparse fast Fourier transform(HSFFT).The algorithm first replaces the IFFT process of the traditional parallel code phase capture algorithm with inverse sparse fast Fourier transform(ISFFT)with better computing performance,and then uses linear search combined with code phase discrimination to replace the positioning loop and the estimation loop with poor noise immunity in ISFFT.Theoretical analysis and simulation results show that,compared with the existing SFFT parallel code phase capture algorithm,the calculation amount of this algorithm is reduced by 19%,and the SNR performance is improved by about 5dB.Compared with the classic FFT parallel code phase capture algorithm,the calculation amount of the algorithm in this paper is reduced by 43%,and when the capture probability is greater than 95%,the SNR performance of the two is approximately the same.
基金supported by a grant from 2022 National Natural Science Foundation of China project“Research on key technology of generalization of human-computer collaborative learning ability based on domain adaptation algorithm”.(No.62277002)。
文摘The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications.On the technical line,the cross-modal AI generation application based on human feedback system is accelerated.In the business model,the scenes to realize interactive functions are constantly enriched.This paper reviews the evolution process of AIGC,closely follows the current situation of the coexistence of business acceleration and technical worries in the application of artificial intelligence education,analyzes the application of AIGC education in 7 subdivided fields,and analyzes the optimization direction of application cases from the perspective of perception-cognition-creation technology maturity matrix.The 3 recommendations and 2 follow-up research directions will promote the scientific application of artificial intelligence education in the AIGC period.
基金supported in part by the National Natural Science Foundation of China(No.61701197)in part by the open research fund of State Key Laboratory of Integrated Services Networks(No.ISN23-11)+3 种基金in part by the National Key Research and Development Program of China(No.2021YFA1000500(4))in part by the 111 Project(No.B23008)in part by the Future Network Scientific Research Fund Project(FNSRFP2021-YB-11)in part by the project of Changzhou Key Laboratory of 5G+Industrial Internet Fusion Application(No.CM20223015)。
文摘Federated edge learning(FEEL)technology for vehicular networks is considered as a promising technology to reduce the computation workload while keeping the privacy of users.In the FEEL system,vehicles upload data to the edge servers,which train the vehicles’data to update local models and then return the result to vehicles to avoid sharing the original data.However,the cache queue in the edge is limited and the channel between edge server and each vehicle is time-varying.Thus,it is challenging to select a suitable number of vehicles to ensure that the uploaded data can keep a stable cache queue in edge server while maximizing the learning accuracy.Moreover,selecting vehicles with different resource statuses to update data will affect the total amount of data involved in training,which further affects the model accuracy.In this paper,we propose a vehicle selection scheme,which maximizes the learning accuracy while ensuring the stability of the cache queue,where the statuses of all the vehicles in the coverage of edge server are taken into account.The performance of this scheme is evaluated through simulation experiments,which indicates that our proposed scheme can perform better than the known benchmark scheme.
基金National Science Foundation of China(NSFC)(61871082 and 62111530150)Fundamental Research Funds for the Central Universities(ZYGX2020ZB043 and ZYGX2019J008).
文摘As the emergence of various highbandwidth services and the requirements to support 5G/Wi-Fi 6 wireless networks,the next generation fixed networks,i.e.F5G,are expected to be realized in the 5G era.F5G is endowed with new characteristics,including ultra-high bandwidth,all-optical connections and optimal service experience.With the prospect of optical-to-everywhere,optical technologies are used for mobile front-haul,mid-haul,and back-haul.Optical access networks would play an important role in F5G to support radio access network and fixed access network.Low-latency PON is a key for cost effective-haul traffic aggregation.In terms of signal transmission,intensity modulation directdetection(IM-DD)is a promising scheme due to its simple architecture.The fundamental challenge associated with direct-detection is the disappearance of the transmitted signal’s phase.In access network,the flexibility and low latency are the two key factors affecting service experience.In this article,we review the evolution of PONs and the challenges of current PONs in detail.We analyze key enabling digital signal processing(DSP)techniques,including detection linearization for direct-detection and simplified coherent detection,adaptive equalizers,digital filer enabled flexible access network and low-latency inter-ONU communications.Finally,we discuss the developing trends of future optical access networks.
文摘This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We aim to maximize the throughput overall GTs by jointly optimizing the UAVs’trajectory,the GTs’scheduling and power allocation.Unlike most prior studies,we consider the UAVs’turning and climbing angle constraints,the UAVs’three-dimensional(3D)trajectory constraints,minimum UAV-to-UAV(U2U)distance constraint,and the GTs’transmit power requirements.However,the formulated problem is a mixed-integer non-convex problem and is intractable to work it out with conventional optimization methods.To tackle this difficulty,we propose an efficient robust iterative algorithm to decompose the original problem be three sub-problems and acquire the suboptimal solution via utilizing the block coordinate descent(BCD)method,successive convex approximation(SCA)technique,and S-procedure.Extensive simulation results show that our proposed robust iterative algorithm offers a substantial gain in the system performance compared with the benchmark algorithms.
基金supported in part by the National Science Foundation of China under Grant 62101253the Natural Science Foundation of Jiangsu Province under Grant BK20210283+2 种基金the Jiangsu Provincial Inno-vation and Entrepreneurship Doctor Program under Grant JSSCBS20210158the Open Research Foun-dation of National Mobile Communications Research Laboratory under Grant 2022D08the Research Foundation of Nanjing for Returned Chinese Scholars.
文摘Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks,but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated.To this end,this article discusses the concepts of edge intelligence from the semantic cognitive perspective.Two instructive theoretical models for edge semantic cognitive intelligence(ESCI)are first established.Afterwards,the ESCI framework orchestrating deep learning with semantic communication is discussed.Two representative applications are present to shed light on the prospect of ESCI in 6G networks.Some open problems are finally listed to elicit the future research directions of ESCI.
基金supported by National Natural Science Foundation of China(No.92067202,No.62001049,&No.62071058)Beijing Natural Science Foundation under Grant 4222012Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the separated optimization paradigm.In this context,this paper provides a comprehensive tutorial that overview how joint source-channel coding(JSCC)can be employed for improving overall system performance.For the purpose,we first introduce the communication requirements and performance metrics for 6G.Then,we provide an overview of the source-channel separation theorem and why it may not hold in practical applications.In addition,we focus on two new JSCC schemes called the double low-density parity-check(LDPC)codes and the double polar codes,respectively,giving their detailed coding and decoding processes and corresponding performance simulations.In a nutshell,this paper constitutes a tutorial on the JSCC scheme tailored to the needs of future 6G communications.
基金National Key RD Program of China Grant(2018YFB1801504)the President Funding of China Academy of Engineering Physics with No.YZJJLX2018009.
文摘In terahertz communication,the direct frequency conversion structure in which orthogonal mixer is the main frequency conversion unit,makes engineers get into trouble of in-phase(I)branch and quadrature(Q)branch imbalance,carrier wave leakage,etc.These damages result in system performance tremendous degrades.We proposed a semiblind method to estimate the I/Q imbalance of THz orthogonal modulator,based on predefined preamble and pilot symbols for quadrature amplitude modulation(QAM).In this paper,a transmitter with Y band quadrature mixer and 20Gbps base-band signal has been tested.The bandwidth of the baseband signal was 7GHz,and the modulation type was 16QAM.By this method,7dB improvement of the system’s symbol Mean Square Error(MSE)has been got.That means the proposed method can be used to eliminate the I/Q imbalance effectively.
基金the National Nat-ural Science Foundation of China under Grants 61771163the Natural Science Foundation for Out-standing Young Scholars of Heilongjiang Province un-der Grant YQ2020F001the Science and Technol-ogy on Communication Networks Laboratory under Grants SXX19641X072 and SXX18641X028.(Cor-respondence author:Min Jia)。
文摘Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme.
基金supported by the National Natural Science Foundation of China under Grant No.61901099, 61972076, 61973069 and 62061006the Natural Science Foundation of Hebei Province under Grant No.F2020501037the Natural Science Foundation of Guangxi under Grant No.2018JJA170167
文摘Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliability and efficiency of data sharing need to be further enhanced.Federated learning allows the server to exchange parameters without obtaining private data from clients so that the privacy is protected.Broad learning system is a novel artificial intelligence technology that can improve training efficiency of data set.Thus,we propose a federated bidirectional connection broad learning scheme(FeBBLS)to solve the data sharing issues.Firstly,we adopt the bidirectional connection broad learning system(BiBLS)model to train data set in vehicular nodes.The server aggregates the collected parameters of BiBLS from vehicular nodes through the federated broad learning system(FedBLS)algorithm.Moreover,we propose a clustering FedBLS algorithm to offload the data sharing into clusters for improving the aggregation capability of the model.Some simulation results show our scheme can improve the efficiency and prediction accuracy of data sharing and protect the privacy of data sharing.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grants No.61801299 and No.61372077in part by the Shenzhen Science and Technology Program under Grants GJHZ 20180418190529516 and JSGG 20180507183215520。
文摘The terahertz(THz)antennas,which have features of small size,wide frequency bandwidth and high data rate,are important devices for transmitting and receiving THz electromagnetic waves in the emerging THz systems.However,most of THz antennas suffer from relatively high loss and low fabrication precision due to their small sizes in high frequency bands of THz waves.Therefore,this paper presents a detailed overview of the most recent research on the performance improvement of THz antennas.Firstly,the development of THz antennas is briefly reviewed and the basic design ideas of THz antennas are introduced.Then,THz antennas are categorized as metallic antennas,dielectric antennas and new material antennas.After that,the latest research progress in THz photoconductive antennas,THz horn antennas,THz lens antennas,THz microstrip antennas and THz on-chip antennas are discussed.In particular,the practical difficulties for the development of THz antennas are discussed with promising approaches.In addition,this paper also presents a short review of the process technology of THz antennas.Finally,the vital challenges and the future research directions for THz antennas are presented.
基金National Natural Science Foundation of China (61871241, 61771263)Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX18-2422)+3 种基金Six Categories Talent Peak of Jiangsu Province (KTHY-039)Science and Technology Program of Nantong (JC2018127, JC2018129, GY22017013)Stereoscopic Coverage Communication Network Verification Platform for China Sea (PCL2018KP002)Open Research Fund of Nantong University-Nantong Joint Research Center for Intelligent Information Technology (KFKT2017A05, KFKT2017B02)
文摘In this paper, we investigate a joint beamforming and time switching(TS) design for an energy-constrained cognitive two-way relay(TWR) network. In the network, the energy-constrained secondary user(SU) relay employs TS protocol to harvest energy from the signals sent by the circuit-powered primary user(PU) transmitter, and then exploits the harvested energy to perform information forwarding. Our aim is to maximize the sum rate of SUs under the constraints of the data rate of PU, the energy harvesting and the transmit power of the SU relay. To determine the beamforming matrix and TS ratio, we decouple the original non-convex problem into two subproblems which can be solved by semidefinite relaxation and successive convex optimization methods. Furthermore, we derive closed form expressions of the optimal solutions for each subproblem, which facilitates the design of a suboptimal iterative algorithm to handle the original sum rate maximization problem. Simulation results are presented to illustrate the effectiveness and superior performance of the proposed joint design against other conventional schemes in the literature.