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6G Space-Air-Ground Communication Networks and Key Technologies

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 24541

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Prof. Tiejun Lv

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Guest Editor

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: signal processing; communications; theory and networking

Dr. Jie Zeng

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Guest Editor

School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Interests: 5G/6G; URLLC; satellite communications

Prof. Dr. Xin Su

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Guest Editor

Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Interests: broadband wireless access; wireless and mobile network architecture; self-organizing network; software-defined radio; cooperative communications

Special Issue Information

Dear Colleagues,

Recently, we have seen a growing interest in space–air–ground integrated networks (SAGINs), which are a -dimensional hierarchical networks based on the ground network and expanded by the space-based network. In the face of future demand for wide-area smart connectivity and global random access, 6G will present a breakthrough in key technologies, including network architecture and air interface, to build an integrated space–air–ground communication system and realize omnidirectional wireless access. Software defined networking (SDN) is believed to remain a key technology in SAGINs, as it has the advantage of enabling centralized and scalable control, sensing and computing. Recent advances introduce the existing space–air–ground communication systems and the diversified application scenarios oriented for the future smart society and the presentation an overall architecture.

This Special Issue therefore aims to put together original research and review articles on recent advances, technologies, solutions and applications, and new challenges in the design of the network architecture, waveform and multi-access in the field of SAGINs systems.

Potential topics include but are not limited to:

new modulation and multi-access;
multi-beam collaborative transmission;
satellite-ground collaborative transmission;
Spectrum sharing and interference coordination;
end-to-end slicing;
mobility management;
phased-array antenna;
communication and navigation integration;
space–air–ground integrated service;
physical layer security in SAGINs;
software-defined networking;
network management;
Network security and privacy.

Prof. Dr. Tiejun Lv
Dr. Jie Zeng
Prof. Dr. Xin Su
Guest Editors

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Published Papers (11 papers)

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Research

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24 pages, 3352 KiB

Open AccessArticle

Satellite Network Security Routing Technology Based on Deep Learning and Trust Management

by Zhiguo Liu, Junlin Rong, Yingru Jiang and Luxi Zhang

Sensors 2023, 23(20), 8474; https://doi.org/10.3390/s23208474 - 15 Oct 2023

Cited by 1 | Viewed by 1102

Abstract

The conventional trust model employed in satellite network security routing algorithms exhibits limited accuracy in detecting malicious nodes and lacks adaptability when confronted with unknown attacks. To address this challenge, this paper introduces a secure satellite network routing technology founded on deep learning and trust management. The approach embraces the concept of distributed trust management, resulting in all satellite nodes in this paper being equipped with trust management and anomaly detection modules for assessing the security of neighboring nodes. In a more detailed breakdown, this technology commences by preprocessing the communication behavior of satellite network nodes using D–S evidence theory, effectively mitigating interference factors encountered during the training of VAE modules. Following this preprocessing step, the trust vector, which has undergone prior processing, is input into the VAE module. Once the VAE module’s training is completed, the satellite network can assess safety factors by employing the safety module during the collection of trust evidence. Ultimately, these security factors can be integrated with the pheromone component within the ant colony algorithm to guide the ants in discovering pathways. Simulation results substantiate that the proposed satellite network secure routing algorithm effectively counters the impact of malicious nodes on data transmission within the network. When compared to the traditional trust management model of satellite network secure routing algorithms, the algorithm demonstrates enhancements in average end-to-end delay, packet loss rate, and throughput. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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17 pages, 3570 KiB

Open AccessArticle

Cluster Content Caching: A Deep Reinforcement Learning Approach to Improve Energy Efficiency in Cell-Free Massive Multiple-Input Multiple-Output Networks

by Fangqing Tan, Yuan Peng and Qiang Liu

Sensors 2023, 23(19), 8295; https://doi.org/10.3390/s23198295 - 7 Oct 2023

Viewed by 754

Abstract

With the explosive growth of micro-video applications, the transmission burden of fronthaul and backhaul links is increasing, and meanwhile, a lot of energy consumption is also generated. For reducing energy consumption and transmission delay burden, we propose a cell-free massive multiple-input multiple-output (CF-mMIMO) system in which the cache on the access point (AP) is used to reduce the load on the link. In this paper, a total energy efficiency (EE) model of a cache-assisted CF-mMIMO system is established. When optimizing EE, forming the co-operation cluster is critical. Therefore, we propose an energy-efficient joint design of content caching, AP clustering, and low-resolution digital-to-analog converter (DAC) in a cache-assisted CF-mMIMO network based on deep reinforcement learning. This scheme can effectively cache content in APs and select the appropriate DAC resolution. Then, taking into account the channel state information and user equipment (UE)’s content request preference, a deep deterministic policy gradient algorithm is used to jointly optimize the cache strategy, AP clustering, and DAC resolution decisions. Simulation results show that the energy efficiency of the proposed scheme is 4% higher than that of other schemes without the resolution optimization and is much higher than that of the only AP clustering without the joint design of content caching and channel quality. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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17 pages, 863 KiB

Open AccessArticle

A Federated Learning Latency Minimization Method for UAV Swarms Aided by Communication Compression and Energy Allocation

by Liang Zeng, Wenxin Wang and Wei Zuo

Sensors 2023, 23(13), 5787; https://doi.org/10.3390/s23135787 - 21 Jun 2023

Cited by 1 | Viewed by 1177

Abstract

Unmanned aerial vehicle swarms (UAVSs) can carry out numerous tasks such as detection and mapping when outfitted with machine learning (ML) models. However, due to the flying height and mobility of UAVs, it is very difficult to ensure a continuous and stable connection between ground base stations and UAVs, as a result of which distributed machine learning approaches, such as federated learning (FL), perform better than centralized machine learning approaches in some circumstances when utilized by UAVs. However, in practice, functions that UAVs must perform often, such as emergency obstacle avoidance, require a high sensitivity to latency. This work attempts to provide a comprehensive analysis of energy consumption and latency sensitivity of FL in UAVs and present a set of solutions based on an efficient asynchronous federated learning mechanism for edge network computing (EAFLM) combined with ant colony optimization (ACO) for the cases where UAVs execute such latency-sensitive jobs. Specifically, UAVs participating in each round of communication are screened, and only the UAVs that meet the conditions will participate in the regular round of communication so as to compress the communication times. At the same time, the transmit power and CPU frequency of the UAV are adjusted to obtain the shortest time of an individual iteration round. This method is verified using the MNIST dataset and numerical results are provided to support the usefulness of our proposed method. It greatly reduces the communication times between UAVs with a relatively low influence on accuracy and optimizes the allocation of UAVs’ communication resources. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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11 pages, 3263 KiB

Open AccessArticle

DoSDefender: A Kernel-Mode TCP DoS Prevention in Software-Defined Networking

by Dongbin Wang, Yu Zhao, Hui Zhi, Dongzhe Wu, Weihan Zhuo, Yueming Lu and Xu Zhang

Sensors 2023, 23(12), 5426; https://doi.org/10.3390/s23125426 - 8 Jun 2023

Viewed by 898

Abstract

The limited computation resource of the centralized controller and communication bandwidth between the control and data planes become the bottleneck in forwarding the packets in Software-Defined Networking (SDN). Denial of Service (DoS) attacks based on Transmission Control Protocol (TCP) can exhaust the resources of the control plane and overload the infrastructure of SDN networks. To mitigate TCP DoS attacks, DoSDefender is proposed as an efficient kernel-mode TCP DoS prevention framework in the data plane for SDN. It can prevent TCP DoS attacks from entering SDN by verifying the validity of the attempts to establish a TCP connection from the source, migrating the connection, and relaying the packets between the source and the destination in kernel space. DoSDefender conforms to the de facto standard SDN protocol, the OpenFlow policy, which requires no additional devices and no modifications in the control plane. Experimental results show that DoSDefender can effectively prevent TCP DoS attacks in low computing consumption while maintaining low connection delay and high packet forwarding throughput. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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21 pages, 3191 KiB

Open AccessArticle

Graph Neural Network-Based Efficient Subgraph Embedding Method for Link Prediction in Mobile Edge Computing

by Xiaolong Deng, Jufeng Sun and Junwen Lu

Sensors 2023, 23(10), 4936; https://doi.org/10.3390/s23104936 - 20 May 2023

Cited by 1 | Viewed by 1837

Abstract

Link prediction is critical to completing the missing links in a network or to predicting the generation of new links according to current network structure information, which is vital for analyzing the evolution of a network, such as the logical architecture construction of MEC (mobile edge computing) routing links of a 5G/6G access network. Link prediction can provide throughput guidance for MEC and select appropriate c nodes through the MEC routing links of 5G/6G access networks. Traditional link prediction algorithms are always based on node similarity, which needs predefined similarity functions, is highly hypothetical and can only be applied to specific network structures without generality. To solve this problem, this paper proposes a new efficient link prediction algorithm PLAS (predicting links by analysis subgraph) and its GNN (graph neural network) version PLGAT (predicting links by graph attention networks) based on the target node pair subgraph. In order to automatically learn the graph structure characteristics, the algorithm first extracts the h-hop subgraph of the target node pair, and then predicts whether the target node pair will be linked according to the subgraph. Experiments on eleven real datasets show that our proposed link prediction algorithm is suitable for various network structures and is superior to other link prediction algorithms, especially in some 5G MEC Access networks datasets with higher AUC (area under curve) values. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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13 pages, 407 KiB

Open AccessCommunication

Optimal Designs of SVC-Based Content Placement and Delivery in Wireless Caching Networks

by Xuewei Zhang, Lin Zhang, Yuan Ren, Jing Jiang and Junxuan Wang

Sensors 2023, 23(10), 4823; https://doi.org/10.3390/s23104823 - 17 May 2023

Cited by 1 | Viewed by 991

Abstract

To allieviate the heavy traffic burden over backhaul links and improve the user’s quality of service (QoS), edge caching plays an important role in wireless networks. This paper investigated the optimal designs of content placement and transmission in wireless caching networks. The contents to be cached and requested were encoded into individual layers by scalable video coding (SVC), and different sets of layers can provide different viewing qualities to end users. The demanded contents were provided by helpers caching the requested layers, or by the macro-cell base station (MBS) otherwise. In the content placement phase, this work formulated and solved the delay minimization problem. In the content transmission phase, the sum rate optimization problem was established. To effectively solve the nonconvex problem, the methods of semi-definite relaxation (SDR), successive convex approximation (SCA), and arithmetic-geometric mean (AGM) inequality were adopted, after which the original problem was transformed into the convex form. The numerical results show that the transmission delay is reduced by caching contents at helpers. Moreover, the fast convergence of the proposed algorithm for solving the sum rate maximization problem is presented, and the sum rate gain of edge caching is also revealed, as compared to the benchmark scheme without content caching. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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11 pages, 1069 KiB

Open AccessArticle

Rethinking LEO Mega-Constellation Routing to Provide Fast Internet Access Services

by Zijian Yang, Feng Tian, Jifeng Jin and Huijie Liu

Sensors 2023, 23(6), 3207; https://doi.org/10.3390/s23063207 - 17 Mar 2023

Cited by 1 | Viewed by 1875

Abstract

In the realm of providing space-based internet access services, utilizing large-scale low Earth orbit (LEO) satellite networks have emerged as a promising solution for bridging the digital divide and connecting previously unconnected regions. The deployment of LEO satellites can augment terrestrial networks, with increased efficiency and reduced costs. However, as the size of LEO constellations continues to grow, the routing algorithm design of such networks faces numerous challenges. In this study, we present a novel routing algorithm, designated as Internet Fast Access Routing (IFAR), aimed at facilitating faster internet access for users. The algorithm consists of two main components. Firstly, we develop a formal model that calculates the minimum number of hops between any two satellites in the Walker-Delta constellation, along with the corresponding forwarding direction from source to destination. Then, a linear programming is formulated, to match each satellite to the visible satellite on the ground. Upon receipt of user data, each satellite then forwards the data only to the set of visible satellites that correspond to its own satellite. To validate the efficacy of IFAR, we conduct extensive simulation work, and the experimental results showcase the potential of IFAR to enhance the routing capabilities of LEO satellite networks and improve the overall quality of space-based internet access services. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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23 pages, 1456 KiB

Open AccessArticle

An Efficient Multi-Dimensional Resource Allocation Mechanism for Beam-Hopping in LEO Satellite Network

by Shengjun Guo, Kai Han, Wenbin Gong, Lu Li, Feng Tian and Xinglong Jiang

Sensors 2022, 22(23), 9304; https://doi.org/10.3390/s22239304 - 29 Nov 2022

Cited by 2 | Viewed by 3359

Abstract

Low Earth Orbit (LEO) satellite communication networks have become an important means to provide internet access services for areas with limited infrastructure. Compared with the Geostationary Earth Orbit (GEO) satellites, the LEO satellites have limited on-board communication caching and calculating resources. Furthermore, the distribution of traffic requests is dynamically changing and uneven due to the relative movement between the LEO satellites and the ground. Therefore, how to schedule the multi-dimensional resources is an important issue for the LEO satellite communication networks. Beam-hopping is an efficient approach to improve the resource utilization by dynamically allocating time, power, and frequency according to the traffic requests. This paper proposes an efficient multi-dimensional resource allocation mechanism for beam-hopping in LEO satellite networks, which simultaneously satisfies the GEO interference avoidance. First, we construct the beam-hopping model of LEO satellites, and formulate the resource optimization problem. Second, we provide the weighted greedy strategy to determine the illumination pattern. In order to reduce the search space, the cells are clustered to non-interference clusters. Then, an improved genetic algorithm is provided to jointly allocate the communication resources. Finally, we construct various simulations to evaluate our proposed mechanism. Compared with the random-BH, polling-BH and traditional genetic algorithm, our algorithm achieves better performance in terms of both system throughput, access success rate, average delay and fairness between cells. The performance improvement is more significant in scenarios where traffic demand is unevenly distributed. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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25 pages, 818 KiB

Open AccessArticle

Traffic Load Optimization for Multi-Satellite Relay Systems in Space Information Network: A Proportional Fairness Approach

by Xudong Zhong, Baoquan Ren, Xiangwu Gong and Hongjun Li

Sensors 2022, 22(22), 8806; https://doi.org/10.3390/s22228806 - 14 Nov 2022

Viewed by 1218

Abstract

Backbone satellites in a space information network (SIN) can be used as air base stations or data relay satellites (DRSs) to realize cross-system, cross-network and long-distance relay transmission. In this paper, a traffic load optimization problem for multi-satellite relay systems in SIN is considered to achieve highly efficient cooperative transmission and improve resource utility. A model of SIN based on a distributed satellite cluster (DSC) is considered, and the characteristics of the model are analyzed. Based on this, a hybrid resource management architecture combining distributed and central resources control schemes is proposed to realize a centrally controllable and distributed optimization of resources to meet various comprehensive service requirements. Two scenarios of multi-satellite relay systems in SIN are given, and traffic load optimization problems with joint bandwidth and power allocation for these two scenarios are formulated based on proportional fairness (PF) criterion to achieve traffic load balancing with considerable system capacity. The optimization problems in these two scenarios are proved to be a convex optimization problem with mathematical analysis, and the closed-form solutions of two problems in their dual domain are derived by dual transformation. With the closed-form solutions, two iterative algorithms based on the subgradient method are designed under the proposed hybrid resource management architecture to solve the problems in this paper. Simulation results show that the proposed schemes can effectively improve the upper bound of system capacity by resource sharing and cooperative relay, and it can balance the traffic load well with guarantees of a reasonable level system capacity compared with existing methods. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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15 pages, 1624 KiB

Open AccessArticle

A Cooperative Routing Scheme Using Inter-Satellite Links to Assist Data Downloading for LEO Satellite Networks

by Zijian Yang, Huijie Liu, Jifeng Jin and Feng Tian

Sensors 2022, 22(20), 7986; https://doi.org/10.3390/s22207986 - 19 Oct 2022

Cited by 1 | Viewed by 2405

Abstract

Low earth orbit (LEO) satellite networks can provide Internet service to users in areas where cellular networks are difficult to deploy. One critical function of satellites is to transfer data from satellite networks to ground core network through earth stations (ESs). The Ka-band multiple-input multiple-output (MIMO) can be used to establish feeder links with larger bandwidth between satellites and ESs. However, propagation at the Ka band is subjected to rain attenuation and various atmospheric fading mechanisms, which severely reduce the maximum link capacity. As a result, the insufficient capacity of feed link becomes the throughput bottleneck of satellite networks. In order to increase network throughput, it is important to fully use feeder link resources. In this paper, we propose a cooperation scheme to route packets to ESs through a well-resourced feeder link, such that the bandwidth of the feeder links can be fully utilized and the throughput of data downloading at the ESs is maximized. Firstly, we model the satellite network system and the feeder link based on MIMO technology. Then, a Maximum-Flow-Minimum-Cost (MCMF) routing algorithm consisting of two Linear Programs (LPs) is presented to compute maximum-flow routings for data download. Eventually, a variety of simulations are conducted to assess the proposed scheme, which shows that the cooperative routing scheme outperforms the existing SiRRS method in terms of throughput and delay. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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Review

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42 pages, 1013 KiB

Open AccessReview

Hybrid Satellite–Terrestrial Networks toward 6G: Key Technologies and Open Issues

by Syed Bilal Raza Tirmizi, Yunfei Chen, Subhash Lakshminarayana, Wei Feng and Aziz A. Khuwaja

Sensors 2022, 22(21), 8544; https://doi.org/10.3390/s22218544 - 6 Nov 2022

Cited by 14 | Viewed by 7464

Abstract

Future wireless networks will be required to provide more wireless services at higher data rates and with global coverage. However, existing homogeneous wireless networks, such as cellular and satellite networks, may not be able to meet such requirements individually, especially in remote terrain, including seas and mountains. One possible solution is to use diversified wireless networks that can exploit the inter-connectivity between satellites, aerial base stations (BSs), and terrestrial BSs over inter-connected space, ground, and aerial networks. Hence, enabling wireless communication in one integrated network has attracted both the industry and the research fraternities. In this work, we provide a comprehensive survey of the most recent work on hybrid satellite–terrestrial networks (HSTNs), focusing on system architecture, performance analysis, design optimization, and secure communication schemes for different cooperative and cognitive HSTN network architectures. Different key technologies are compared. Based on this comparison, several open issues for future research are discussed. Full article

(This article belongs to the Special Issue 6G Space-Air-Ground Communication Networks and Key Technologies)

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