Big Data Application Simulation Platform Design for Onboard Distributed Processing of LEO Mega-Constellation Networks

Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.

DetSpace:Distributed Congestion Free Routing for Global Deterministic Network in Mega-Constellations

Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in small-scale networks through centralized computing and resource reservation,they cannot be applied on a global scale.The emerging mega-constellations enable new opportunities for realizing deterministic delay globally.As one constellation(e.g.,Starlink)might be managed by a single operator(e.g.,SpaceX),packets can be routed within deterministic number of hops.Moreover,the path diversity brought by the highly symmetrical network structure in mega-constellations can help to construct a congestion free network by routing.This paper leverages these unique characteristics of mega-constellations to avoid the traditional network congestion caused by multiple inputs and single output,and to determine the routing hops,and thus realizing a global deterministic network(DETSPACE).The model based on the 2D Markov chain theoretically verifies the correctness of DETSPACE.The effectiveness of DETSPACE in different traffic load con-ditions is also verified by extensive simulations.

For Mega-Constellations: Edge Computing and Safety Management Based on Blockchain Technology

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.

Mega-Constellations Based TT&C Resource Sharing: Keep Reliable Aeronautical Communication in an Emergency

With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.

Accurately tracking hypersonic gliding vehicles via an LEO mega-constellation in relay tracking mode

In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the developing megaconstellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above problem.The whole tracking mission is composed of several tracking intervals with the same duration.Within each tracking interval,several appropriate satellites are dispatched to track the HGV.Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion.The tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by simulation.The results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking arc.Moreover,the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.

HOI延迟对LEO卫星简化动力学POD的影响

通常使用无电离层(IF)线性组合(LC)消除低地球轨道(LEO)卫星简化动力学精密定轨(POD)一阶电离层延迟误差,忽略了高阶电离层(HOI)延迟误差。随着LEO卫星POD技术的发展,计算不同轨道高度的HOI延迟并探索其变化已成为进一步提高POD精度的重要手段。首先,使用国际参考电离层-2016(IRI-2016)和国际地磁参考场第13代(IGRF-13)模型,计算电离层穿刺点(IPP)位置和地磁场强度。其次,使用平滑星载GNSS数据计算电离层斜路径总电子含量(STEC)。然后,分别计算GOCE、GRACE-A和SWARM-A/B卫星的二阶和三阶电离层延迟。最后,评估了HOI延迟对LEO卫星重叠轨道分析、卫星激光测距(SLR)检核和精密科学轨道(PSO)比较结果的影响。实验结果表明:HOI延迟对LEO卫星简化动力学POD的影响大约在毫米至厘米的数量级上;HOI延迟对LEO卫星简化动力学POD外符合精度的影响分别达到0.92,0.22,0.21和0.18 mm;随着LEO卫星轨道高度的增加,HOI延迟对LEO卫星简化动力学POD的影响减小。

LEO卫星系统对GSO卫星系统干扰规避技术研究

近年,低地轨道(Low Earth Orbit,LEO)卫星星座繁荣发展,LEO卫星系统和地球静止轨道(Geosynchronous Orbit,GSO)卫星系统同频共用情况非常普遍,同频段内LEO卫星系统需要规避GSO卫星系统的上下行干扰。LEO卫星系统对GSO卫星系统干扰规避方法和策略包含调整指向、更改频率、降低功率和关闭波束。在对系统干扰规避模式及干扰区域情况进行仿真基础上,结合LEO卫星系统特点,提出经过规避区域时切换信关站或者馈电链路关闭下行波束的方案。用户链路结合相控阵天线特点,信令波束通过上注星载相控阵天线波位表实现干扰规避;业务波束通过上注干扰规避区域对应的地面网格编码实现干扰规避,提出不同链路干扰规避实施方案和实现流程。

LEO多星座增强BDS精密单点定位性能评估

针对不同构型的低轨星座(LEO)增强北斗卫星导航系统BDS的精密单点定位PPP性能开展研究。通过IGS高、中、低纬度6测站实测数据、精密轨道及钟差产品,生成BDS、“鸿雁”HY、“微厘空间”CS精密星历、卫星钟差、观测量等实验仿真数据,构建了LEO增强BDS PPP数学模型,实现了BDS、BDS+HY、BDS+CS、BDS+HY+CS不同组合PPP。实验结果表明,在10、60 min静态PPP定位精度以及平均可视卫星数、PDOP值等方面均有不同程度的提升,HY对高纬度KIRU站改善效果显著,收敛时间减至2 min以内,CS对低纬度FAA1站测站收敛时间的提升最大,从46 min 50 s缩短至2 min,HY+CS增强BDS的效果最好,10 min定位精度均能达到毫米级,除FAA1站外其他测站均收敛在1 min以内。

LEO-RAN切片场景联合用户关联和动态资源分配算法

为了解决6G天地一体化网络的资源高效利用问题,提出了一种面向高密度低地球轨道卫星-无线接入网(LEO-RAN)切片场景的联合用户关联和动态资源分配算法。考虑不同切片的最小速率、最大时延及资源比例等约束,以频谱效率(SE)和不同切片服务水平协议(SLA)满意率(SSR)的加权和作为优化目标,建立用户关联和资源分配的联合优化问题。首先设计基于多智能体深度确定性策略梯度(MADDPG)的网络切片算法确定切片资源比例,然后采用基于拉格朗日对偶的用户关联算法确定最优的用户关联策略,最后通过轮询调度机制将资源分配给用户。仿真结果表明,所提算法在满足不同切片差异化SLA的同时能够有效提高SE。与基于MADDPG-RA、MATD3-LG、MATD3-RA、MASAC-LG和MASAC-RA算法相比,所提算法系统效用分别提升了2.0%、2.3%、5.7%、8.7%和9.4%。

巨型LEO星座的时不变拓扑与航点路由设计

LEO卫星网是6G空地一体通信的重要组成部分,在带来低成本广覆盖等应用优势的同时,面临高动态和快切换等技术挑战。虽然卫星规律运动,星座图时变性也有章可循,但天基网的规模远高于地面网,不能简单延用因特网现有路由技术。综合应用快照变换和虚拟节点法,以卫星及星际链路为参考系,通过3步位置变换和极区收缩处理,得到巨型LEO星座的时不变拓扑,证明完全格网的适用性,并应用航点路由机制设计了本地卫星固定式路由算法,进一步给出了格网星座与循环图的同构性以及结构优化的探索方向。

基于区块链的GEO/LEO卫星网络安全认证技术研究

由于卫星网络高暴露、高时延的特点,不同系统星座组网进行遥控指令发布及遥测信息回传时,容易受到其他卫星恶意接入导致信息泄露。卫星网络安全认证成为天基测控实现过程中必须解决的技术问题。面向高轨和低轨双层卫星网络场景下的安全组网需求,提出了一种基于区块链的星间组网认证技术,该技术包括基于区块链的卫星身份认证和星间消息认证。研究设计将卫星临时身份登记上区块链,通过比对链上信息完成卫星的身份认证。为进一步增强消息传输安全性,采用椭圆曲线数字签名算法对星间消息进行签名验证。通过仿真分析,验证了所提技术能够以较小的时间开销满足卫星在组网认证阶段的多种安全需求。

LEO航天器太阳电池阵激光诱导电弧放电试验与分析

基于太阳电池阵空间电弧放电理论,对纳秒脉冲激光诱导太阳电池阵电弧放电机理进行分析,采用空间放电模拟试验系统,试验研究了低地球轨道(LEO)等离子体环境下纳秒脉冲激光诱导太阳电池阵电弧放电的功率密度阈值及其放电特性。试验结果表明:LEO等离子体环境下激光诱导太阳电池阵电弧放电的功率密度阈值约为1.08×10^(8)W/cm^(2),与无激光诱导相比,放电持续时间增加了20%,且每施加1次纳秒脉冲激光诱导电弧放电概率约为60%。对比分析不同工况下的太阳电池阵损伤效应可得:纳秒脉冲激光诱导电弧放电破坏绝缘层最严重,容易造成太阳电池阵中部分PN结短路失效,其损坏程度远远大于空间环境太阳电池串间电弧放电烧蚀损坏效应和盖玻片表面热应力损伤造成的PN结断路失效。此结论可为航天器太阳电池阵放电试验的措施及试验参数选取提供参考。

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

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.

LEO星载GPS实时精密定轨伪模糊度随机过程参数优化

提出在定轨策略及其他变量不变的情况下,使用一种数值步进的搜索比较方法,以确定伪模糊度随机过程参数的最优设置。使用GRACE-C、SWARM-A两颗LEO卫星2021年doy92~101共10 d的GPS数据及同时段的CNT、MADOCA两种实时精密星历产品,以模拟在轨实时精密定轨的方式,对伪模糊度随机过程参数开展优化实验。结果表明,在伪模糊度参数最优值方案下,两颗LEO卫星的实时精密定轨三维位置误差(RMS)约为4.62~7.56 cm,相比于传统模糊度浮点解方案,使用CNT和MADOCA产品的实时定轨精度分别平均提升约39.15%和29.61%。

基于状态转移张量的LEO目标短期误差传播及碰撞概率计算

目前低轨区域空间目标数量不断增加且航天器轨道机动能力越来越强。结合LEO机动目标快速碰撞预警对于计算效率和计算精度的需求,在J2模型假设下,提出了一种基于状态转移张量的短期状态误差传播方法。该方法从航天器相对运动的角度,引入二阶状态转移张量来描述误差传播的非线性特征,给出了误差传播的近似解析表达式,在此基础上完成了碰撞概率计算。仿真结果表明:提出的方法对于LEO目标短期误差传播及碰撞概率计算具有良好的计算效率和计算精度。

OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

Multi-network-region traffic cooperative scheduling in large-scale LEO satellite networks

A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

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.

Dynamic access task scheduling of LEO constellation based on space-based distributed computing

A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process under a series of complex constraints,which is important for enhancing the matching between resources and requirements.A complex algorithm is not available because that the LEO on-board resources is limi-ted.The proposed genetic algorithm(GA)based on two-dimen-sional individual model and uncorrelated single paternal inheri-tance method is designed to support distributed computation to enhance the feasibility of on-board application.A distributed system composed of eight embedded devices is built to verify the algorithm.A typical scenario is built in the system to evalu-ate the resource allocation process,algorithm mathematical model,trigger strategy,and distributed computation architec-ture.According to the simulation and measurement results,the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91%in a typical scene.The response time is decreased by 40%com-pared with the conditional GA.