Multi-layered Satellite Networks Research Articles

An Efficient Differentiated Routing Scheme for MEO/LEO-Based Multi-Layer Satellite Networks

An Efficient Differentiated Routing Scheme for MEO/LEO-Based Multi-Layer Satellite Networks

An intelligent encryption decision method for autonomous domain of multilayer satellite network

Multi-layer satellite network (MLSN) is an important part of the Space-Air-Ground Integrated Network (SAGIN), it has obvious advantages in coverage density, business processing, service efficiency and other comprehensive capabilities compared with ordinary single-layer satellite networks. However, due to the fact that many space nodes, highly dynamic topology changes and wireless links scattered in free space, MLSNs are facing the dual challenges of inefficient organization and lack of security. In this case, this paper considers providing secure encryption decision support for the return of data obtained by low earth orbit (LEO) observation satellites relying on the local autonomous region of multi-layer satellite space. By quantifying the security strength of encryption algorithms, the work to be optimized is described as the problem of maximizing the security strength under the constraint of return delay of the data. This paper thus proposes a solution based on deep reinforcement learning (DRL), which relies on reasonably setting the key supporting elements such as state, action and reward closely related to the problem to achieve fast and reliable decision output, and the simulation results show that the proposed method has better performance than many comparison methods.

Resource Allocation and Offloading Strategy for UAV-Assisted LEO Satellite Edge Computing

In emergency situations, such as earthquakes, landslides and other natural disasters, the terrestrial communications infrastructure is severely disrupted and unable to provide services to terrestrial IoT devices. However, tasks in emergency scenarios often require high levels of computing power and energy supply that cannot be processed quickly enough by devices locally and require computational offloading. In addition, offloading tasks to server-equipped edge base stations may not always be feasible due to the lack of infrastructure or distance. Since Low Orbit Satellites (LEO) have abundant computing resources, and Unmanned Aerial Vehicles (UAVs) have flexible deployment, offloading tasks to LEO satellite edge servers via UAVs becomes straightforward, which provides computing services to ground-based devices. Therefore, this paper investigates the computational tasks and resource allocation in a UAV-assisted multi-layer LEO satellite network, taking into account satellite computing resources and device task volumes. In order to minimise the weighted sum of energy consumption and delay in the system, the problem is formulated as a constrained optimisation problem, which is then transformed into a Markov Decision Problem (MDP). We propose a UAV-assisted airspace integration network architecture, and a Deep Deterministic Policy Gradient and Long short-term memory (DDPG-LSTM)-based task offloading and resource allocation algorithm to solve the problem. Simulation results demonstrate that the solution outperforms the baseline approach and that our framework and algorithm have the potential to provide reliable communication services in emergency situations.

An analysis method for ISL of multilayer constellation

The multilayer satellite network has high spatial spectrum utilization, flexible networking, strong survivability, and diversified functions. The inter-satellite links (ISLs) and cross-layer ISLs (CLISLs) enable direct communication paths between satellites, which improves the spatial autonomy of the constellation. Due to the existence of perturbation, ISLs are affected for a long time, which impacts reliable inter-satellite transmission. The stability and complexity of ISL establishment are related to the static and dynamic characteristics of range and azimuth. This paper presents a model of ISLs in a perturbed multilayer constellation. Series of theoretical derivation, simulation, and numerical calculation are carried out. A more comprehensive multilayer constellation ISL model is obtained. The work of this paper provides some theoretical foundations for constellation networking research.

Service function path selection methods for multi-layer satellite networks

Service function path selection methods for multi-layer satellite networks

Performance Analysis of Cooperative Nonorthogonal Multiple Access Scheme in Two-Layer GEO/LEO Satellite Network

Multilayer satellite networks (MLSNs) are viewed as a promising framework of the future satellite communication networks by realizing cooperative communication among satellites in different orbits. In this article, we introduce the cooperative nonorthogonal multiple access (C-NOMA) scheme into a two-layer geostationary Earth orbit/low Earth orbit satellite network in a frequency coexistence scenario and investigate the performance of the considered network. Taking into account the dynamic properties and channel characteristic of the satellite nodes, we first establish the generic architecture and then obtain the equivalent end-to-end signal-to-interference-plus-noise ratios along with the feasible region of power allocation coefficients based on the C-NOMA principle. Furthermore, the analytical expressions of the system ergodic capacity and outage probability are derived and approximated using Meijer-G functions to evaluate the system performance efficiently. Finally, simulation results are provided to attest the validity of the theoretical results as well as show the superiority of the C-NOMA scheme and the impact of various parameters on the system performance.

A Review of Routing Algorithms Based on Multi-Layer Satellite Networks

Compared with single layer satellite network, satellite distribution of multi-layer satellite networks in the double layer or multilayer orbital plane, combines all the advantages of engaging subjects of the satellite, therefore contains its low vulnerability, good robustness, high stability, high spectrum efficiency and system throughput, channel characteristics such as large capacity, in the satellite network is a very promising direction. Multilayer satellite network also has some inevitable disadvantages, that is, the number of nodes and the number of links is large, so it has the characteristics of frequent changes in network topology, which requires higher routing algorithm. There are many researches on routing algorithms based on multi-layer satellite networks at home and abroad. This paper introduces the general situation of multi-layer satellite network, classifies the existing routing algorithms of multi-layer satellite network according to different standards, analyzes several typical routing algorithms in detail, points out the advantages and disadvantages, and summarizes the future development trend.

Dynamic Resource Pricing and Allocation in Multilayer Satellite Network

The goal of delivering high-quality service has spurred research of 6G satellite communication networks. The limited resource-allocation problem has been addressed by next-generation satellite communication networks, especially multilayer networks with multiple low-Earth-orbit (LEO) and non-low-Earth-orbit (NLEO) satellites. In this study, the resource-allocation problem of a multilayer satellite network consisting of one NLEO and multiple LEO satellites is solved. The NLEO satellite is the authorized user of spectrum resources and the LEO satellites are unauthorized users. The resource allocation and dynamic pricing problems are combined, and a dynamic game-based resource pricing and allocation model is proposed to maximize the market advantage of LEO satellites and reduce interference between LEO and NLEO satellites. In the proposed model, the resource price is formulated as the dynamic state of the LEO satellites, using the resource allocation strategy as the control variable. Based on the proposed dynamic game model, an open-loop Nash equilibrium is analyzed, and an algorithm is proposed for the resource pricing and allocation problem. Numerical simulations validate the model and algorithm.

Joint User Pairing and Power Allocation for NOMA-Based GEO and LEO Satellite Network

Multi-layer satellite networks (MLSNs) is of great potential for the integrated 5G networks to provide diversified services. However, MLSNs confront frequency interference coordination problem between satellite systems in different orbits. This paper investigates a joint user pairing and power allocation scheme in a non-orthogonal multiple access (NOMA)-based geostationary earth orbit (GEO) and low earth orbit (LEO) satellite network. Specifically, a novel NOMA framework with two uplink receivers, i.e. the GEO and LEO satellites is established where the NOMA groups are formed considering the subcarrier assignment of ground users. To maximize the system capacity, an optimization problem is then introduced subject to the decoding threshold and power consumption. Since the formulated problem is non-convex and mathematically intractable, we decompose it into user pairing and power allocation schemes. In the user pairing scheme, virtual GEO users are generated to transform the multi-user pairing problem into a matching problem and a max-min pairing strategy is adopted to ensure the fairness among NOMA groups. In the power allocation scheme, the non-convex problem is transformed into multiple convex subproblems and solved by iterative algorithm. Simulation results validate the effectiveness and superiority of the proposed schemes when compared with several existing schemes.

Structural Performance of Satellite Networks: A Complex Network Perspective

Network structure has significant impact on its data transmission and robustness. This article presents a framework to evaluate the structure performance of dynamic networks, with a focus on measuring the topological dynamics and assessing its effect on routing, transmission efficiency, network robustness, and network capacity. Based on this framework, the structural performance of satellite networks including both single-layered and multilayered satellite networks is evaluated systematically. The performance results reveal that it is difficult to design the efficient and feasible transmission protocols for multilayered satellite networks for their high-dynamic topologies with irregular changes, which brings unpractical requirements on the routing update. To cope with this problem, a synchronization mechanism of the interorbital links for multilayered satellite networks is presented, which can significantly reduce and regularize the topological dynamics of multilayered satellite networks. Its advantages can effectively facilitate the realization of transmission protocols for multilayered satellite networks. Finally, the experimental evaluation results demonstrate the effectiveness of the proposed strategy.

Reinforcement Learning Based Capacity Management in Multi-Layer Satellite Networks

The development of satellite networks is drawing much more attention in recent years due to the wide coverage ability. Composed of geosynchronous orbit (GEO), medium earth orbit (MEO), and low earth orbit (LEO) satellites, the satellite network is a three-layer heterogeneous network of high complexity, for which comprehensive theoretical analysis is still missing. In this paper, we investigate the problem of capacity management in the three-layer heterogeneous satellite network. We first construct the model of the network and propose a low-complexity method for calculating the capacity between satellites. Based on the time structure of the time expanded graph, the searching space is greatly reduced compared to traditional augmenting path searching strategies, which can significantly reduce the computing complexity. Then, based on Q-learning, we proposed a long-term optimal capacity allocation algorithm to optimize the long-term utility of the system. In order to reduce the storage and computing complexity, a learning framework with low-complexity is constructed while taking the properties of satellite systems into account. Finally, we analyze the capacity performance of the three-layer heterogeneous satellite network and also evaluate the proposed algorithms with numerical results.

Load Balancing Based on Cache Resource Allocation in Satellite Networks

During a high-speed movement, the satellites are connected intermittently, so the queue length becomes larger and a cache overflow appears. In this paper, the abundant storage resources of the multilayered satellite network (MLSN) are used to avoid the packet loss caused by a cache overflow of the Low Earth Orbit (LEO) satellites. However, due to the limited storage space of the Geostationary Earth Orbit (GEO) satellites, an effective load balance scheme which addresses two problems: LEO satellites competition in a non-cooperative fashion and content popularity utilization, is needed. Therefore, we propose a load balancing scheme based on the Stackelberg game, containing Members of a Game Algorithm and Distributed Cache Price Bargaining Algorithm. In addition, a storage technology based on content popularity (Popularity Matching Algorithm) is introduced. The numerical results show that the proposed methods are effective in pricing, cache resource allocation of GEO satellites, and load balancing of LEO satellites.

Space-terrestrial integrated mobility management via named data networking

In Future Space-Terrestrial Integrated Networks (FSTINs), mobility is the norm rather than the exception, the current TCP/IP architecture is not competent. As a promising future network architecture, Named Data Networking (NDN) can support content consumer mobility naturally, but the content producer mobility support remains a challenging problem. Most previous research simply considered this problem in terrestrial scenarios, which involve stable infrastructures to achieve node mobility management. In this paper, we consider the problem in an FSTIN scenario without special handover management infrastructures. Specifically, we propose a tracing-based producer mobility management scheme and an addressing-assisted forwarding method via NDN architecture. We formally describe Multi-Layered Satellite Networks via a Time Varying Graph model and define the foremost path calculating problem to calculate the route of space segment, as well as an algorithm that can function in both dense (connected) and sparse (delay/disruption tolerant) scenarios. Finally, we discuss the acceleration method that can improve the Space-Terrestrial Integrated forwarding efficiency. Performance evaluation demonstrates that the proposed scheme can support fast handover and efficient forwarding in the FSTIN scenario.

Multi-objective network optimization combining topology and routing algorithms in multi-layered satellite networks

Multi-objective network optimization combining topology and routing algorithms in multi-layered satellite networks

Distributed contact plan design for multi-layer satellite-terrestrial network

In multi-layer satellite-terrestrial network, Contact Graph Routing (CGR) uses the contact information among satellites to compute routes. However, due to the resource constraints in satellites, it is extravagant to configure lots of the potential contacts into contact plans. What's more, a huge contact plan makes the computing more complex, which further increases computing time. As a result, how to design an efficient contact plan becomes crucial for multi-layer satellite network, which usually has a large scaled topology. In this paper, we propose a distributed contact plan design scheme for multi-layer satellite network by dividing a large contact plan into several partial parts. Meanwhile, a duration based inter-layer contact selection algorithm is proposed to handle contacts disruption problem. The performance of the proposed design was evaluated on our Identifier/Locator split based satellite-terrestrial network testbed with 79 simulation nodes. Experiments showed that the proposed design is able to reduce the data delivery delay.

Network coding‐based multi‐path routing algorithm in two‐layered satellite networks

Satellite networks are capable of contenting a variety of data transmission needs of users in geographically diverse locations throughout the world. Multi-layered satellite networks (MLSNs) can construct efficient communications networks due to their extensive coverage and high network capacity. However, throughput degradation and severe end-to-end delay could occur in MLSNs because of the traffic congestion. To resolve these problems, the authors first propose a novel MEO/LEO satellite network architecture that construct effective inter-satellite links. Then the authors present a network coding-based multi-path routing algorithm to deliver traffic through the hybrid satellite network. The analysis of characteristics of the proposed scheme are addressed by performance evaluations in simulation.

Markov approximation for multilayered selection in satellite network

A satellite network system comprises three layers of satellites: LEO (Low Earth Orbit), MEO (Middle Earth Orbit) and GEO (Geostationary Orbit). In the system, users can choose a layer according to their demands, including QoS (Quality of Service), congestion, energy cost, etc. The utility that users gain will change when they access satellites in different layers. The mobility of satellites in the LEO and MEO leads to frequent handover among satellites in the same layer. These characteristics of multi-layered satellite networks make it possible for us to exploit the optimal distribution of users, which will maximize the utility of the entire satellite network. While the proposed problem is an NP-hard problem, we analyze the system based on the Markov chain and use the Markov approximation to approach the maximum utility. In addition, we use the count down and select algorithm to implement the process of Markov chain. The simulation results validate the convergence of the Markov approximation. In addition, the gap between the approximate value and optimal values decreases with an increase in ß, which is a positive constant in Markov formulation, according to the simulation results.

Capacity of two-layered satellite networks

Satellite networks have great potential in providing global ubiquitous broadband communication. In this paper, we explore the capacity of both single-layered and two-layered satellite networks. Closed-form approximate expressions of network capacity are derived, which provide insights into the impact of different network parameters, such as number of orbits, number of satellites in each orbit, link bandwidth, existence of the seam, the relative position between the two layers, etc. We investigate the advantages of two-layered structure by comparing the capacity of single-layered and two-layered networks. The results show that the network capacity of two-layered networks is always no less than the total capacity of the two layers. Moreover, we obtain the network parameter condition under which the network capacity of two-layered networks is strictly larger than the sum capacity of the two layers. The results obtained in this paper can serve as a guideline for the design of efficient multi-layered satellite networks.

A Novel Traffic Control Scheme for Multi-Layered Satellite Network Based on Chain Reaction Model

Multi-Layered Satellite Network (MLSN) is a kind of delay tolerant network with characters of intermittent connection, long packet queuing time, complex and uncertain delay time, etc. The call congestion rate of new business is higher in delay tolerant network which leads to the reduction of communication quality and the high packet loss rate. The existing traffic control scheme is hard to meet the individual requirements of new business. It becomes more and more important to study the most effective traffic control scheme so as to increase the satellite bandwidth utilization. According to the nuclear chain reaction of atomic physics, a novel traffic control method based on chain reaction model (TCCR) is presented in this paper to realize dynamic data transmission and control for MLSN. The optimal flow distribution scheme will be obtained by analyzing the network transmission information in this algorithm. Simulation by OPENT is done which proves that TCCR can obviously improve the network total throughput, shorten link transmission delay, and reduce packet loss rate of MLSN.

Investigation of frame mode unification and virtual channel multiplexing based on the multilayered satellite network OISLs interface

In a multi-layered optical satellite network, a standardized data transmission is a reliable guarantee to efficiently process and transfer multi-service data for the space link. The transmission frame reframing unit (TFRU) is proposed to solve the problem of different service data having low transmission efficiency in the laser link. The TFRU uses a virtual channel (VC) technology to unify the format and rate of transmitted data using second encapsulation and VC scheduling for the service data. The Priority VC schedule algorithm is proposed to further improve multiplex efficiency. According to the principle of TFRU encapsulation and arrival rate of service data, the frame dynamic priority is defined by the VC priority and frame criticality. Furthermore, the Priority VC schedule specific method is provided. The simulation results show that the throughput increases to 3.0546M, and the scheduling time delay reduces to 0.9183s. Thus, the system performance has been greatly enhanced. The cache demands are satisfied because the laser terminal data transmission rate is larger than the sum of all service data rates. Using the dynamic schedule generated TFRU frames, the priority algorithm based on the TFRU ensures frame scheduling fairness in each VC.