Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity comm...Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.展开更多
In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit...In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.展开更多
A satellite communication system consisting of small earth terminals which utilize spread spectrum multiple access (SSMA) techniques is introduced in this paper. Having no master station, the system is distributively ...A satellite communication system consisting of small earth terminals which utilize spread spectrum multiple access (SSMA) techniques is introduced in this paper. Having no master station, the system is distributively controlled. The frequency band used is 6/4GHz.展开更多
In this paper,we investigate a spectrumsensing system in the presence of a satellite,where the satellite works as a sensing node.Considering the conventional energy detection method is sensitive to the noise uncertain...In this paper,we investigate a spectrumsensing system in the presence of a satellite,where the satellite works as a sensing node.Considering the conventional energy detection method is sensitive to the noise uncertainty,thus,a temporal convolutional network(TCN)based spectrum-sensing method is designed to eliminate the effect of the noise uncertainty and improve the performance of spectrum sensing,relying on the offline training and the online detection stages.Specifically,in the offline training stage,spectrum data captured by the satellite is sent to the TCN deployed on the gateway for training purpose.Moreover,in the online detection stage,the well trained TCN is utilized to perform real-time spectrum sensing,which can upgrade spectrum-sensing performance by exploiting the temporal features.Additionally,simulation results demonstrate that the proposed method achieves a higher probability of detection than that of the conventional energy detection(ED),the convolutional neural network(CNN),and deep neural network(DNN).Furthermore,the proposed method outperforms the CNN and the DNN in terms of a lower computational complexity.展开更多
Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-increasing demands for higher throughput,lower latency,and wider coverage.However,spectrum scarcity places obstacles in the susta...Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-increasing demands for higher throughput,lower latency,and wider coverage.However,spectrum scarcity places obstacles in the sustainable development.To accommodate the expanding network within a limited spectrum,spectrum sharing is deemed as a promising candidate.Particularly,cognitive radio(CR)has been proposed in the literature to allow satellite and terrestrial networks to share their spectrum dynamically.However,the existing CR-based schemes are found to be impractical and inefficient because they neglect the difficulty in obtaining the accurate and timely environment perception in satellite communications and only focus on link-level coexistence with limited interoperability.In this paper,we propose an intelligent spectrum management framework based on software defined network(SDN)and artificial intelligence(AI).Specifically,SDN transforms the heterogenous satellite and terrestrial networks into an integrated satellite and terrestrial network(ISTN)with reconfigurability and interoperability.AI is further used to make predictive environment perception and to configure the network for optimal resource allocation.Briefly,the proposed framework provides a new paradigm to integrate and exploit the spectrum of satellite and terrestrial networks.展开更多
By cognitive radio,the low Earth orbit(LEO) satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks...By cognitive radio,the low Earth orbit(LEO) satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks(CRNs).The competition can be regarded as a game and analyzed with game theory.This particular unlicensed spectrum sharing problem is modeled here,and the special properties of "spatially-distinguished-interference" and the short period of the interactions between satellites and terrestrial CRNs are explored.Then,the problem is formulated as a "partially-blind" finitely repeated prisoner's dilemma by game theory.Finally,we begin with two promising spectrum sharing schemes,which can be used to enforce the frequency reuse among the remotely located terrestrial CRN players as well as to overcome the observation noise.By analysis and comparison,it is proposed that the novel refreshing-contrite-tit-for-tat(R-CTFT) is the optimal spectrum sharing scheme.Simulation results verify that it can be used to utilize the spectrum most efficiently.展开更多
文摘Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.
文摘In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.
文摘A satellite communication system consisting of small earth terminals which utilize spread spectrum multiple access (SSMA) techniques is introduced in this paper. Having no master station, the system is distributively controlled. The frequency band used is 6/4GHz.
基金the National Science Foundation of China (No.91738201, 61971440)the Jiangsu Province Basic Research Project (No.BK20192002)+1 种基金the China Postdoctoral Science Foundation (No.2018M632347)the Natural Science Research of Higher Education Institutions of Jiangsu Province (No.18KJB510030)。
文摘In this paper,we investigate a spectrumsensing system in the presence of a satellite,where the satellite works as a sensing node.Considering the conventional energy detection method is sensitive to the noise uncertainty,thus,a temporal convolutional network(TCN)based spectrum-sensing method is designed to eliminate the effect of the noise uncertainty and improve the performance of spectrum sensing,relying on the offline training and the online detection stages.Specifically,in the offline training stage,spectrum data captured by the satellite is sent to the TCN deployed on the gateway for training purpose.Moreover,in the online detection stage,the well trained TCN is utilized to perform real-time spectrum sensing,which can upgrade spectrum-sensing performance by exploiting the temporal features.Additionally,simulation results demonstrate that the proposed method achieves a higher probability of detection than that of the conventional energy detection(ED),the convolutional neural network(CNN),and deep neural network(DNN).Furthermore,the proposed method outperforms the CNN and the DNN in terms of a lower computational complexity.
基金National Natural Science Foundation of China(61631005)National Natural Science Foundation of China(U1801261)+3 种基金National Natural Science Foundation of China(61571100)National Key R&D Program of China(2018YFB1801105)Central Universities(ZYGX2019Z022)Programme of Introducing Talents of Discipline to Universities(B20064)。
文摘Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-increasing demands for higher throughput,lower latency,and wider coverage.However,spectrum scarcity places obstacles in the sustainable development.To accommodate the expanding network within a limited spectrum,spectrum sharing is deemed as a promising candidate.Particularly,cognitive radio(CR)has been proposed in the literature to allow satellite and terrestrial networks to share their spectrum dynamically.However,the existing CR-based schemes are found to be impractical and inefficient because they neglect the difficulty in obtaining the accurate and timely environment perception in satellite communications and only focus on link-level coexistence with limited interoperability.In this paper,we propose an intelligent spectrum management framework based on software defined network(SDN)and artificial intelligence(AI).Specifically,SDN transforms the heterogenous satellite and terrestrial networks into an integrated satellite and terrestrial network(ISTN)with reconfigurability and interoperability.AI is further used to make predictive environment perception and to configure the network for optimal resource allocation.Briefly,the proposed framework provides a new paradigm to integrate and exploit the spectrum of satellite and terrestrial networks.
文摘By cognitive radio,the low Earth orbit(LEO) satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks(CRNs).The competition can be regarded as a game and analyzed with game theory.This particular unlicensed spectrum sharing problem is modeled here,and the special properties of "spatially-distinguished-interference" and the short period of the interactions between satellites and terrestrial CRNs are explored.Then,the problem is formulated as a "partially-blind" finitely repeated prisoner's dilemma by game theory.Finally,we begin with two promising spectrum sharing schemes,which can be used to enforce the frequency reuse among the remotely located terrestrial CRN players as well as to overcome the observation noise.By analysis and comparison,it is proposed that the novel refreshing-contrite-tit-for-tat(R-CTFT) is the optimal spectrum sharing scheme.Simulation results verify that it can be used to utilize the spectrum most efficiently.