Orthogonal Time Frequency and Space (OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio (SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator (RBFSD) based on the pseudo-noise (PN) sequence. The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than −15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.
{"title":"High-precision Doppler frequency estimation based positioning using OTFS modulations by red and blue frequency shift discriminator","authors":"Shaojing Wang, Xiaomei Tang, Jing Lei, Chunjiang Ma, Chao Wen, Guangfu Sun","doi":"10.23919/JCC.fa.2023-0229.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0229.202402","url":null,"abstract":"Orthogonal Time Frequency and Space (OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio (SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator (RBFSD) based on the pseudo-noise (PN) sequence. The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than −15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140462787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access (RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.
{"title":"Energy-efficient traffic offloading for RSMA-based hybrid satellite terrestrial networks with deep reinforcement learning","authors":"Qingmiao Zhang, Lidong Zhu, Yanyan Chen, Shan Jiang","doi":"10.23919/JCC.fa.2023-0454.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0454.202402","url":null,"abstract":"As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access (RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2021-0823.202402
Yan Li, Shaoyi Xu, Yunpu Wu, Dongji Li
This paper investigates the data collection in an unmanned aerial vehicle (UAV)-aided Internet of Things (IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight (LoS) channel. Especially, access points (APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors' scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation (SCA) scheme is applied to solve each non-convex subproblem. Finally, the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.
{"title":"Flight time minimization of UAV for cooperative data collection in probabilistic LoS channel","authors":"Yan Li, Shaoyi Xu, Yunpu Wu, Dongji Li","doi":"10.23919/JCC.fa.2021-0823.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2021-0823.202402","url":null,"abstract":"This paper investigates the data collection in an unmanned aerial vehicle (UAV)-aided Internet of Things (IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight (LoS) channel. Especially, access points (APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors' scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation (SCA) scheme is applied to solve each non-convex subproblem. Finally, the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2023-0107.202402
Peizhong Xie, Junjie Jiang, Ting Li, Yin Lu
The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables. An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method, and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.
{"title":"Joint optimization of resource allocation and trajectory based on user trajectory for UAV-assisted backscatter communication system","authors":"Peizhong Xie, Junjie Jiang, Ting Li, Yin Lu","doi":"10.23919/JCC.fa.2023-0107.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0107.202402","url":null,"abstract":"The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables. An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method, and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2023-0138.202402
Jia Zhu, Junsheng Mu, Yuanhao Cui, Xia Jing
In this paper, we focus on the power allocation of Integrated Sensing and Communication (ISAC) with orthogonal frequency division multiplexing (OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is, to maximize the mutual information (MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals, as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However, the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization (AO), sequence convex programming (SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.
{"title":"Mutual information maximization via joint power allocation in integrated sensing and communications system","authors":"Jia Zhu, Junsheng Mu, Yuanhao Cui, Xia Jing","doi":"10.23919/JCC.fa.2023-0138.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0138.202402","url":null,"abstract":"In this paper, we focus on the power allocation of Integrated Sensing and Communication (ISAC) with orthogonal frequency division multiplexing (OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is, to maximize the mutual information (MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals, as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However, the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization (AO), sequence convex programming (SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140470244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2023-0635.202402
Peng Wei, W. Feng, Yunfei Chen, Ning Ge, Wei Xiang
Networked robots can perceive their surroundings, interact with each other or humans, and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle (UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links, via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener's Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage, enabling new orchestration between network serving and positive mobility control of robots. Moreover, the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing (MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.
{"title":"Robot-oriented 6G satellite-UAV networks: Requirements, paradigm shifts, and case studies","authors":"Peng Wei, W. Feng, Yunfei Chen, Ning Ge, Wei Xiang","doi":"10.23919/JCC.fa.2023-0635.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0635.202402","url":null,"abstract":"Networked robots can perceive their surroundings, interact with each other or humans, and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle (UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links, via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener's Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage, enabling new orchestration between network serving and positive mobility control of robots. Moreover, the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing (MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140467897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2021-0759.202402
Yueyue Su, Nan Qi, Zanqi Huang, Rugui Yao, Luliang Jia
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.
{"title":"Cooperative anti-jamming and interference mitigation for UAV networks: A local altruistic game approach","authors":"Yueyue Su, Nan Qi, Zanqi Huang, Rugui Yao, Luliang Jia","doi":"10.23919/JCC.fa.2021-0759.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2021-0759.202402","url":null,"abstract":"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.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140467409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2023-0404.202402
Zhen Zhang, Bing Guo, Chengjie Li
In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication. While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.
{"title":"For mega-constellations: Edge computing and safety management based on blockchain technology","authors":"Zhen Zhang, Bing Guo, Chengjie Li","doi":"10.23919/JCC.fa.2023-0404.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0404.202402","url":null,"abstract":"In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication. While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCC.fa.2023-0424.202402
Ning Yang, Heng Wang, Jingming Hu, Bangning Zhang, D. Guo, Yuan Liu
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.
{"title":"Blockchain-based MCS detection framework of abnormal spectrum usage for satellite spectrum sharing scenario","authors":"Ning Yang, Heng Wang, Jingming Hu, Bangning Zhang, D. Guo, Yuan Liu","doi":"10.23919/JCC.fa.2023-0424.202402","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0424.202402","url":null,"abstract":"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.","PeriodicalId":504777,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140470039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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