Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO sate...Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.展开更多
In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signal...In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.展开更多
LEO satellite communication network has a large number of satellites distributed in low orbits,which leads to multiple coverage of many areas on the ground.It is hard work to describe and evaluate the reliability of L...LEO satellite communication network has a large number of satellites distributed in low orbits,which leads to multiple coverage of many areas on the ground.It is hard work to describe and evaluate the reliability of LEO satellite communication network.To solve this problem,the reliability of all-user terminals in LEO satellite communication network is defined,and the corresponding reliability evaluation method is proposed in the paper.Due to the large scale of the interstellar network,a modular reduction algorithm using the modular network instead of the original network for state decomposition is proposed in this paper.Case study shows that the calculation time of the proposed method is equivalent to 6.28%of the original state space decomposition algorithm.On this basis,the reliability of LEO satellite communication network is further analyzed.It is found that the reliability of LEO satellite network was more sensitive to the reliability of Inter-Satellite link and the satisfaction of global coverage in the early stage,and it is more sensitive to the reliability of the satellite in the later stage.The satellite-ground link has a relatively constant impact on of LEO satellite network.展开更多
Driven by improvements in satellite internet and Low Earth Orbit(LEO)navigation augmenta-tion,the integration of communication and navigation has become increasingly common,and further improving navigation capabilitie...Driven by improvements in satellite internet and Low Earth Orbit(LEO)navigation augmenta-tion,the integration of communication and navigation has become increasingly common,and further improving navigation capabilities based on communication constellations has become a significant challenge.In the context of the existing Orthogonal Frequency Division Multiplexing(OFDM)communication systems,this paper proposes a new ranging signal design method based on an LEO satellite communication constellation.The LEO Satellite Communication Constellation Block-type Pilot(LSCC-BPR)signal is superimposed on the com-munication signal in a block-type form and occupies some of the subcarriers of the OFDM signal for transmission,thus ensuring the continuity of the ranging pilot signal in the time and frequency domains.Joint estimation in the time and frequency domains is performed to obtain the relevant distance value,and the ranging accuracy and communication resource utilization rate are determined.To characterize the ranging performance,the Root Mean Square Error(RMSE)is selected as an evaluation criterion.Simulations show that when the number of pilots is 2048 and the Signal-to-Noise Ratio(SNR)is 0 dB,the ranging accuracy can reach 0.8 m,and the pilot occupies only 50%of the communication subcarriers,thus improving the utilization of communication resources and meeting the public demand for communication and location services.展开更多
A novel bandwidth allocation strategy along with a connection admission control technique was proposed to improve the utilization of network resources.It provides the network with better quality-of-service(QoS)guarant...A novel bandwidth allocation strategy along with a connection admission control technique was proposed to improve the utilization of network resources.It provides the network with better quality-of-service(QoS)guarantees,such as new call blocking probability(CBP)and handoff call drop-ping probability(CDP)in multimedia low earth orbit(LEO)satellite networks.Simulation results show that,compared with other bandwidth allocation schemes,the proposed scheme offers very low call dropping probability for real-time connections while,at the same time,keeping resource utilization high.Finally we discussed the fairness for the borrowed nonreal-time connections under three different channel borrowing methods.展开更多
In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource ...In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.展开更多
基金supported by the National Key R&D Program of China under Grant 2020YFB1807900the National Natural Science Foundation of China (NSFC) under Grant 61931005Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.
基金supported by National Natural Science Foundation of China (62171390)Central Universities of Southwest Minzu University (ZYN2022032,2023NYXXS034)the State Scholarship Fund of the China Scholarship Council (NO.202008510081)。
文摘In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.
基金supported by the projects of the National Natural Science Foundation of China entitled“Reliability growth evaluation and prediction model of large aerospace(72071111)”“Reverse multi variable CF-GERT model and its application for complex equipment development schedule under the background of multi project mixed batch(71801127)”+4 种基金“Research on network of reliability growth of complex equipment under the background of collaborative development(71671091)”supported by a joint project of both the NSFC and the RS of the UK entitled“On grey dynamic scheduling model of complex product based on sensing information of internet of things”(71811530338)support of the Fundamental Research Funds for the Central Universities of China(NC2019003,NP2019104)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX210239)support of a project of Intelligence Introduction Base of the Ministry of Science and Technology(G20190010178).
文摘LEO satellite communication network has a large number of satellites distributed in low orbits,which leads to multiple coverage of many areas on the ground.It is hard work to describe and evaluate the reliability of LEO satellite communication network.To solve this problem,the reliability of all-user terminals in LEO satellite communication network is defined,and the corresponding reliability evaluation method is proposed in the paper.Due to the large scale of the interstellar network,a modular reduction algorithm using the modular network instead of the original network for state decomposition is proposed in this paper.Case study shows that the calculation time of the proposed method is equivalent to 6.28%of the original state space decomposition algorithm.On this basis,the reliability of LEO satellite communication network is further analyzed.It is found that the reliability of LEO satellite network was more sensitive to the reliability of Inter-Satellite link and the satisfaction of global coverage in the early stage,and it is more sensitive to the reliability of the satellite in the later stage.The satellite-ground link has a relatively constant impact on of LEO satellite network.
文摘Driven by improvements in satellite internet and Low Earth Orbit(LEO)navigation augmenta-tion,the integration of communication and navigation has become increasingly common,and further improving navigation capabilities based on communication constellations has become a significant challenge.In the context of the existing Orthogonal Frequency Division Multiplexing(OFDM)communication systems,this paper proposes a new ranging signal design method based on an LEO satellite communication constellation.The LEO Satellite Communication Constellation Block-type Pilot(LSCC-BPR)signal is superimposed on the com-munication signal in a block-type form and occupies some of the subcarriers of the OFDM signal for transmission,thus ensuring the continuity of the ranging pilot signal in the time and frequency domains.Joint estimation in the time and frequency domains is performed to obtain the relevant distance value,and the ranging accuracy and communication resource utilization rate are determined.To characterize the ranging performance,the Root Mean Square Error(RMSE)is selected as an evaluation criterion.Simulations show that when the number of pilots is 2048 and the Signal-to-Noise Ratio(SNR)is 0 dB,the ranging accuracy can reach 0.8 m,and the pilot occupies only 50%of the communication subcarriers,thus improving the utilization of communication resources and meeting the public demand for communication and location services.
基金supported by the National Natural Science Foundation of China(Grant No.60496313).
文摘A novel bandwidth allocation strategy along with a connection admission control technique was proposed to improve the utilization of network resources.It provides the network with better quality-of-service(QoS)guarantees,such as new call blocking probability(CBP)and handoff call drop-ping probability(CDP)in multimedia low earth orbit(LEO)satellite networks.Simulation results show that,compared with other bandwidth allocation schemes,the proposed scheme offers very low call dropping probability for real-time connections while,at the same time,keeping resource utilization high.Finally we discussed the fairness for the borrowed nonreal-time connections under three different channel borrowing methods.
文摘In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.