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.

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.

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.

Jamming-Aided Secure Communication in Ultra-Dense LEO Integrated Satellite-Terrestrial Networks

The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

NOMA-Based Collaborative Beam Hopping Frequency Allocation Mechanism for Future LEO Satellite Systems

Low Earth orbit(LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference(CCI). In the cluster area, a non-orthogonal multiple access(NOMA)-based collaborative beam hopping(NCBH) scheme is proposed to minimize the cell-edge user(CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user(CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user’s received power, transmission rate, and outage probability.

High-Risk LEO Satellite Network Path Detection Based on Spatial and Temporal Delay Anomaly Analysis

The gradual deployment of Low-Earth Orbit(LEO)mega constellations with inter-satellite links(ISLs)promises ubiquitous,low-latency,and high-throughput satellite network services.However,networked LEO satellites with ISLs are also at risk of routing attacks such as hijacking.Existing defenses against route hijacking in terrestrial networks can hardly work for the LEO satellite network due to its high spatiotemporal dynamics.To deal with it,we propose RPD,a high-risk routing path detection method for LEO mega-constellation networks.RPD detects abnormal high-risk LEO network paths by checking the consistency between the path delay and the geographical distance.This is efficiently achieved by combining in-band measurements and out-of-band statistical processing to detect the anomaly of the clustering feature in the reference delay matrix.RPD avoids the recalculation of the header cryptographic marks when the handover occurs,thus greatly reducing the cost and improving the performance of highrisk path detection.Experiments showed that the proposed RPD mechanism achieves an average detection accuracy of 91.64%under normal network conditions,and maintain about 89%even when congestion occurs in multiple areas of the network and measurement noise is considered.In addition,RPD does not require any cryptographic operation on the intermediate node,only minimal communication cost with excellent scalability and deployability.

Resource allocation for uplink grant-free access in beam-hopping based LEO satellite systems

The low earth orbit(LEO) satellite system provides a promising solution for the global coverage of Internet of Things(IoT) services.Confronted with the sporadic uplink transmission from massive IoT terminals, this work investigates the grant-free access scheme and resource allocation algorithm for the beam-hopping(BH) based LEO satellite systems.To improve the packet success rate, the time slots are pre-allocated to each cell according to the number of terrestrial terminals and the probability of packet arrival.When the packets arrive, the terrestrial terminals perform contention-free or contention-based grant-free access with packet repetition in the time slots allocated to their cells.The analytical expression of the packet collision probability for the grant-free access scheme is derived to provide reference for the resource allocation.To reduce the computational complexity, a heuristic resource allocation algorithm is proposed to minimize the maximum cell packet collision probability in the system.Simulation results show that the proposed resource allocation scheme achieves lower packet collision probability and higher resource utilization ratio when compared with the uniform resource allocation scheme.

Beam Position and Beam Hopping Design for LEO Satellite Communications

The numbers of beam positions(BPs)and time slots for beam hopping(BH)dominate the latency of LEO satellite communications.Aiming at minimizing the number of BPs subject to a predefined requirement on the radius of BP,a low-complexity user density-based BP design scheme is proposed,where the original problem is decomposed into two subproblems,with the first one to find the sparsest user and the second one to determine the corresponding best BP.In particular,for the second subproblem,a user selection and smallest BP radius algorithm is proposed,where the nearby users are sequentially selected until the constraint of the given BP radius is no longer satisfied.These two subproblems are iteratively solved until all the users are selected.To further reduce the BP radius,a duplicated user removal algorithm is proposed to decrease the number of the users covered by two or more BPs.Aiming at minimizing the number of time slots subject to the no co-channel interference(CCI)constraint and the traffic demand constraint,a low-complexity CCI-free BH design scheme is proposed,where the BPs having difficulty in satisfying the constraints are considered to be illuminated in priory.Simulation results verify the effectiveness of the proposed schemes.

Challenges,Opportunities,and Future Research in the Integration of 5G/6G Networks,LEO Satellites,and IoT for Environmental Protection and Sustainable Development at ECSTAR

The rapid proliferation of connected IoT(Internet of Things)devices,along with the increasing demand for 5G mobile networks and ubiquitous high-speed connectivity,poses significant challenges in the telecommunications sector.To address these challenges,a comprehensive understanding of the integration of 5G/6G networks and LEO(Low Earth Orbit)satellite networks is required,forming the concept of“integrated networks”.Integration offers valuable advantages,including service continuity,wide-area coverage,and support for critical communications and emerging applications.This paper provides a high-level overview of the convergence of 5G/6G,LEO satellites,and IoT devices,shedding light on the technological challenges and standardization issues associated with the transition from 5G to 6G networks using NTNs(Non-Terrestrial Networks)based on LEO satellites.Furthermore,this research delves into the emerging social issues,potential possibilities,and the paradigm shift from the IoT to the IoI(Internet of Intelligence),which is poised to revolutionize the landscape of 6G wireless networks.By highlighting the interconnectedness of 5G/6G networks,LEO satellite systems,and IoT devices,it underscores the importance of leveraging these converging technologies to address environmental protection and achieve the United Nations SDGs(Sustainable Development Goals).In addition to providing valuable insights for readers seeking to comprehend the convergence of 5G/6G networks,LEO satellite systems,and IoT devices,this paper represents the outcomes of a comprehensive analysis conducted at the ECSTAR(Excellence Center of Space Technology and Research).Through an examination of technological challenges and advancements,it identifies future research directions and potential avenues for exploration at ECSTAR,thereby contributing to a broader understanding of integrated networks and their profound impact on future telecommunications systems.This research serves as a significant resource for advancing the knowledge and discourse surrounding the linkages between the convergence of these technologies,environmental protection,and the pursuit of the SDGs.

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卫星接收天线对北斗三号MEO覆盖性分析

低轨增强系统是将低轨卫星作为卫星导航系统的高精度天基监测站,与中高轨卫星定位系统形成互补,可增强定位的精度和完好性,助力构建GNSS全球天基监测网,同时通过提供高精度导航信号,助力提供全球准实时高精度服务。低轨导航增强系统处在同时同频全双工的工作状态,系统存在同频自干扰信号。针对该情况,首先,分析同频干扰对消技术对天基GNSS接收天线波束宽度的需求;其次,理论推导出GNSS接收天线与BDS-3 MEO卫星覆盖之间的关系,给出LEO卫星GNSS接收天线波束宽度最优值,该值既能最大限度降低同频干扰对消实现复杂度,又能实现LEO卫星作为导航增强的系统需求;最后通过工程实际证明该波束宽度的设置合理性,为后续实际工程起到一定的指导意义。

Core-based Shared Tree Multicast Routing Algorithms for LEO Satellite IP Networks

A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.

Analysis of detection capabilities of LEO reconnaissance satellite constellation based on coverage performance

In the design problem of low earth orbit(LEO) reconnaissance satellite constellation, optimization of coverage performance is the design goal in most current methods. However,in the using process, the user only concerns with the detection capabilities rather than coverage performance. To establish the relationship between these two aspects, the reconnaissance processes of normal stochastic targets are considered and the mathematic models of detection processes are built. The indicators of coverage performance are used to evaluate the detection probability and expectation of detection time delay, which are important factors in reconnaissance constellation estimation viewed from military intelligence discipline. The conclusions confirmed by the final simulation will be useful in LEO reconnaissance constellation design, optimization and evaluation.

Research on handover algorithm to reduce the blocking probability in LEO satellite network

Based on the characteristics of guaranteed handover （GH） algorithm, the finite capacity in one system makes the blocking probability （PB） of GH algorithm increase rapidly in the case of high traffic losd. So, when large amounts of multimedia services are transmitted via a single low earth orbit （LEO） satellite system, the PB of it is much higher. In order to solve the problem, a novel handover scheme defined by multi-tier optimal layer selection is proposed. The scheme sufficiently takes into account the characteristics of double-tier satellite network, which is constituted by LEO satellites combined with medium earth orbit （MEO） satellites, and the multimedia transmitted by such network, so it can augment this systematic capacity and effectively reduces the traffic loed in the LEO which performs GH algorithm. The detailed processes are also presented. The simulation and numerical results show that the approach integrated with GH algorithm achieves a significant improvement in the PB and practicality, as compared to the single LEO layer network.

A Discrete-Time Traffic and Topology Adaptive Routing Algorithm for LEO Satellite Networks

“Minimizing path delay” is one of the challenges in low Earth orbit (LEO) satellite network routing algo-rithms. Many authors focus on propagation delays with the distance vector but ignore the status information and processing delays of inter-satellite links. For this purpose, a new discrete-time traffic and topology adap-tive routing (DT-TTAR) algorithm is proposed in this paper. This routing algorithm incorporates both inher-ent dynamics of network topology and variations of traffic load in inter-satellite links. The next hop decision is made by the adaptive link cost metric, depending on arrival rates, time slots and locations of source-destination pairs. Through comprehensive analysis, we derive computation formulas of the main per-formance indexes. Meanwhile, the performances are evaluated through a set of simulations, and compared with other static and adaptive routing mechanisms as a reference. The results show that the proposed DT-TTAR algorithm has better performance of end-to-end delay than other algorithms, especially in high traffic areas.

Optimization of the Internet of Remote Things Data Acquisition Based on Satellite UAV Integrated Network

In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things(IoRT),we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle(UAV)-low earth orbit(LEO)satellite integrated space-air-ground network,in which the UAV acquires data from massive Internet of Things(IoT)devices in special scenarios.To combine with the actual scenario,we consider two different data types,that is,delay-sensitive data and delay-tolerant data,the transmission mode is accordingly divided into two types.For delay-sensitive data,the data will be transmitted via the LEO satellite relay to the data center(DC)in real-time.For delay-tolerant data,the UAV will store and carry the data until the acquisition is completed,and then return to DC.Due to nonconvexity and complexity of the formulated problem,a multi-dimensional optimization Rate Demand based Joint Optimization(RDJO)algorithm is proposed.The algorithm first uses successive convex approximation(SCA)technology to solve the non-convexity,and then based on the block coordinate descent(BCD)method,the data acquisition efficiency is maximized by jointly optimizing UAV deployment,the bandwidth allocation of IoRT devices,and the transmission power of the UAV.Finally,the proposed RDJO algorithm is compared with the conventional algorithms.Simulation consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation,UAV deployment and the transmission power.

Reliability Evaluation of All-User Terminals in LEO Satellite Communication Network Based on Modular Reduction

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.

A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming in- creasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this al- gorithm are less than that of Shortest Path First (SPF) with different delay bound.

Performance Analysis of MAC Protocol for LEO Satellite Networks

Considering that weak channel collision detection ability, long propagation delay and heavy load in LEO satellite communications, a valid adaptive APRMA MAC protocol was proposed. Different access probability functions for different services were obtained and appropriate access probabilities for voice and data users were updated slot by slot based on the estimation of the voice traffic and the channel status. In the proposed MAC protocol limited wireless resource is allocated reasonably by multiple users and high capacity was achieved. Three performance parameters: voice packet loss probability, average delay of data packets and throughput of data packets were considered in simulation. Finally simulation results demonstrated that the performance of system was improved by the APRMA compared with the conventional PRMA, with an acceptable trade-off between QoS of voice and delay of data.