a comprehensive space-air-ground integrated simulation

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2020 年 9 月第二期鹏城实验室通讯

ABSTRACT: The sixth generation (6G) wireless communications networks are expected to provide global coverage,

enhanced spectrum/energy/cost efficiency, higher data rate, lower latency, etc. Space-air-ground integrated network

(SAGIN), as a promising solution to provide cost-effective, large-scale, and flexible wireless communication services,

is envisioned an indispensable part of 6G networks. Since real-world deployment or testing of SAGIN is impracticable,

an efficient SAGIN simulation platform is requisite. In this newsletter, we present a comprehensive introduction of our

developed SAGIN simulator towards 6G, which supports various mobility traces and services, and protocols of space,

aerial, and terrestrial networks.

KEY WORDS: Space-Air-Ground integrated network 6G Simulation platform

A Comprehensive Space-Air-Ground Integrated Simulation Platform Toward 6G

Shen Xuemin University of Waterloo, Canada

Faced with the big datasets required by extremely heterogeneous networks, diversified communication scenarios, large numbers of antennas and spectrum resources, and new service requirements, the sixth generation (6G) networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and machine learning (ML) technologies. In the 6G communication networks, space-air- ground integrated network (SAGIN) is envisioned as a key solution to provide full coverage of 3-dimensional (3D) spatial network, ubiquitous connection of

users, and real-time sharing of heterogeneous network resources.

As an indispensable tool for both research and development of communication networks, the simulation platform plays a key role in analyzing and evaluating the network, especially in SAGIN where real-world deployment and test can be very expensive. An excellent SAGIN simulation platform is of great significance for verifying communication and resource allocation schemes between different networks, and analyzing the performance index of SAGIN. Considering the complex network architecture, high mobility, dynamic network conditions and demands of SAGIN, how to design a unified simulation platform for SAGINs is an important but challenging issue [1].

I. INTRODUCTION ON SAGIN SIMULATION PLATFORM

1.Significance of SAGIN Simulation Platform

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A SAGIN simulation platform should be capable

of simulating the existing and potential comm-unication and networking protocols, algorithms, control schemes, applications, and services. As shown in Fig. 1, we design the SAGIN simulation platform with three layers, i.e., SAGIN infrastructure layer, network module layer, and control and appl icat ion layer. Each layer has speci f ic functionalities and supports the upper layers. Meanwhile, application programming interfaces (APIs) are designed for extending the simulation platform with specific applications and control algorithms. The details of each layer are described as follows.

1) SAGIN infrastructure: The SAGIN infra-structure layer builds the physical environment of the simulation platform, including the Earth representation, digital map, communication infrastructure, and space, aerial, and ground devices. It also generates and maintains the position and mobility of network nodes. Compared with the ground network simulation, the SAGIN simulation platform can support the three-dimensional position and mobility, such as orbiting of satellites, the swarm and flying trajectory of UAVs, and the movement of ground users and vehicles. The mobility data can be either generated by the simulation platform or imported from different sources by users.

There are numerous existing simulation tools, such as MATLAB, STK, NS2, NS3, VISSIM, Omnet++, Mininet, QualNet, etc. Among them, VISSIM, STK, NS-3 and SNS-3 are several commonly used simulation tools that are suitable for SAGIN simulations.

Until now, most existing works focus on evaluating either one single network segment in space, air, or ground, or the integration of space-ground or air-ground networks. There are extensive works evaluating the performance of terrestrial communications by using MATLAB/Simulink, NS-3, OPNET, and so forth. In [2], MATLAB is used to evaluate the application of unmanned aerial vehicles (UAVs) on providing services for ground users in disaster areas. The simulations on drone-assisted vehicular networks are conducted by combining VISSIM, MATLAB, and NS-2 in [3]. Kawamoto et al. propose a new multi-layered satellite network to minimize the packet delivery delay and conduct simulations by using NS-2 [4]. Jia et al. study satellite-assisted data offloading problems and use STK to obtain simulation results[5].

In spite of these works, since the existing platforms of each network in SAGIN are relatively independent and cannot be directly interconnected and complementary, a comprehensive SAGIN simulation platform that addresses the challenges of integrating the space, aerial, and ground networks is yet to be developed, which motivates our work.

II.DESIGN OF SAGIN SIMULATION PLATFORM

1. An Overview of the Platform

2. Existing SAG Simulation

Fig. 1 The architecture of SAGIN simulation platform.

A Comprehensive Space-Air-Ground Integrated Simulation Platform Toward 6G 学术前沿

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2) Network modules: Notice that SAGIN sup-ports a variety of communication and networking protocols, such as satellite communication, aerial communications, LTE, WiFi, etc. In the simulation platform, such protocols are incorporated in different modules. To support LEO satellite communication, we also implemented a LEO satellite communication module. Via network protocol modularization in the simulation platform, the simulation scenario can be built by simply calling the corresponding modules or functions, and it is easy to modify the existing modules or add new modules to extend the functionality.

3) Network control and application: In the network control and application layer, various control algorithms and SAGIN applications are deployed based on the functions provided by the aforementioned two layers. The function of this layer is to test the application behaviors and evaluate network performance under specific network control algorithms. This layer also supports the APIs, which allows user-defined control algorithms and applications to be evaluated in the simulation platform.

In this subsection, we present the imp-lementation details of the SAGIN simulation platform. Fig . 2 shows the main functions supported in the SAGIN simulation platform and how to implement the simulation platform by integrating existing tools. We employ NS-3 as the core simulator and design efficient parsers and interfaces to connect to other platform components for a unified simulation.

1) Simulation scenario: The simulation scenario includes the configuration of network components, determinations of network topology and node mobility, deployment of network services, etc. As shown in Fig. 2, the simulation scenario is supported by two functions, i.e., heterogeneous access and multi-domain integration.

Heterogeneous access is realized by commu-nication modules in NS-3 and its extension. Some modules like the UAV and the satellite communication modules are customized for more realistic simulations of their specific features, e.g., pathloss models, mobility models, etc. As SNS-3 is a

2. Implementation Details

Fig. 2 The implementation of SAGIN simulation platform.

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In this section, we study a specific case in vehicular communications, i .e. , radio access technology (RAT) selection and control, to show the functions of the SAGIN simulation platform. Fig. 3 shows the simulation scenario, where the area around the campus of the University of Waterloo is considered. Each vehicle is equipped with three different network interfaces: LTE, DSRC and LEO user terminal, to connect to base stations, UAVs, and satellites, respectively. The Iridium satellite constellation is used for LEO satellite communications. By loading the realistic map of the simulation scenario into VISSIM, we can configure the roads, intersections, traffic signals, vehicle types and attributes, and driver behaviors in the VISSIM to generate the realistic vehicle mobility trace for the simulation scenario. In the simulation script, the controller is connected to the satellite gateway station, and the vehicles report the real-time network information via different links to the controller according to the location and network coverage. Then, the control algorithms running in

highly specified extension for simulating the GEO satellite communication over the Europe region, we have modified the SNS-3 extension to support LEO satellite communications, named L-SNS-3 module. According to our knowledge, this is the first LEO satellite communication module in NS3. Multi- domain integration is achieved by integrating the mobility of the space, aerial, and ground network segments through mobility generation tools or mobility datasets. Specifically, we employ VISSIM to generate vehicle mobility traces, and STK to generate satellite orbiting movements, and design a parser to transform the generated files to mobility files which can be recognized and imported by NS-3.

2) Centralized and decentralized control: The network control layer plays two important roles, i.e., controlling the network behaviors, and implementing user-defined applications and control policies.

We deploy network control lers in the network edge and cloud, which control the network behaviors by monitoring the real-time network information in both centralized and decentralized ways. The edge controllers are in charge of controlling the network edge, while the cloud controller coordinates among different edge controllers. We implement P2P links with different delays and data rates to simulate control message transmissions between controllers and different network components. Via these links, the network users report the real-time information such as location, speed, and channel conditions to controllers to make real- time decisions on network behaviors. The control layer also implements user interfaces to realize customized applications and control algorithms. There are a variety of research issues in SAGIN, and the platform allows the platform users to define customized simulation scenarios, subjects, and algorithms. The extendibility comes from the ability of the controller

to collect the real-time network information and to disseminate the control messages. The user-defined resource allocation algorithm, for instance, can thus optimally allocate network resources according to the designed goals and the network information.

3) Core simulation: According to the simul-ation scenario and the network control algorithms, the simulation process is conducted by using NS-3. The NS-3 logging output can monitor or debug the simulation programs. Since the SAGIN simulation platform aims to evaluate the performance of the designed SAGIN communication protocols and control algorithms, we also implement the data parser and analytical tools to study the NS-3 simulation output data.

3. Case Study


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the controller can use the information to make decisions and disseminate them back through the links.

How to implement cloud/edge technologies in the simulation platform remains a challenging issue.

Fig. 3 The simulation scenario in the case study.

III. FUTURE RESEARCH AND DEVELOPMENT

In this article, we have presented a SAGIN simulation platform which integrates multiple network protocols, node mobility, and control algorithms. However, research on SAGINs is still in its infancy, and thus the SAGIN simulation platform requires further improvement to simulate the emerging SAGIN architecture, protocols, and applications. There are several topics for future research and development in the SAGIN simulation platform. The software-defined networking (SDN) and network function virtualization (NFV) technologies have significantly changed the communication network architecture. To evaluate the performance of an SDN/NFV-enabled SAGIN, some open-source frameworks and protocols can be implemented in the simulation platform, such as OpenFlow, OpenStack, Opendaylight, etc. Meanwhile, cloud/edge computing can be incorporated in the SAGINs to meet the varying requirements of a myriad of services and applications.

[1] N. Cheng, W. Quan, W. Shi, H. Wu, Q.

Ye, H. Zhou, W. Zhuang, X. S. Shen, and B.

Bai, A comprehensive simulation platform

for space-air- ground integrated network

【J】, IEEE Wireless Communications,

2020, vol. 27, no. 1, pp. 178–185.

[2] A. Ranjan, B. Panigrahi, H. K. Rath,

P. Misra, and A. Simha, LTE- CAS: LTE-

based criticality aware scheduling for

UAV assisted emergency response【C】, in

Proc. IEEE INFOCOM WKSHPS, Apr. 2018.

[3] W. Shi, H. Zhou, J. Li, W. Xu, N.

Zhang, and X. Shen, “Drone assisted

vehicular networks: Architecture,

challenges and opportunities,” IEEE

Netw. 【J】, 2018, vol. 32, no. 3, pp.

130–137.

[4] Y. Kawamoto, H. Nishiyama, N. Kato,

and N. Kadowaki, A traffic distribution

technique to minimize packet delivery

delay in multilayered satellite

networks, IEEE Trans. Veh. Technol. 【J】,

2013, vol. 62, no. 7, pp. 3315– 3324.

[5] X. Jia, T. Lv, F. He, and H. Huang,

Collaborative data downloading by using

inter-satellite links in LEO satellite

networks, IEEE Trans. Wireless Commun.

【J】,2017,vol.16,no. 3, pp. 1523–1532.

Reference

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一种面向 6G 的空天地一体化网络仿真平台

摘要：第六代（6G）无线通信网络有望提供全球覆盖、更高的频谱 / 能源 / 成本效率、更高的数据速率，

和更低的传输时延等。空天地一体化网络（SAGIN）因其能够提供高性价比、大规模、灵活的无线通信服务，

已经被认为未来 6G 网络中必不可少的一部分。由于无法在现实世界中部署或测试 SAGIN，因此需要提供

一种有效的 SAGIN 仿真平台。在本文中，我们全面介绍了一种面向 6G 开发的 SAGIN 仿真平台，该平台

可以支持各种移动性跟踪和服务以及空间、空中和地面的网络协议。

关键词：空天地一体化网络 6G 仿真平台

沈学民

加拿大滑铁卢大学


a comprehensive space-air-ground integrated simulation

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