Ubiquitous coverage is one of the most important goals for mobile communication networks. To achieve this, integration of space, air, and ground networks is highly demanded, which expects to become the one of the enabling technologies for 6G networks. However, the integrated network faces the demand of orders of magnitude improvement in coverage, access capability and network service capability, which could not be achieved under the existing access and management mechanisms. To support this, artificial intelligence (AI) can be applied to provide technical means for solving the problems of organization and management of the space-air-ground integrated network. By virtualizing and “softwarizing” the resources of the entire network, and provisioning intelligence in the core network elements of the integrated network, the space-air-ground integrated network will be able to form native intelligence. The native intelligence will facilitate a highly autonomous network, which has the capabilities of self-adaptive scale, self-allocation resource, self-learning behaviors and self-evolution function, and is expected to meet diversified, refined and differentiated service quality requirements in the future.

 

The design of a native intelligent space-air-ground integrated network faces many challenges including but not limited to: space-air integrated network architecture, the evolution of network native intelligence, deployment of intelligent network elements in the control plane of the heterogeneous dynamic network, native intelligence based access control/mobile management/connection management, unified novel air interface, end-to-end virtualization technology, service-driven flexible slice customization, etc.

 

The rapid development of various technologies, such as AI and SDN/NFV, big data, digital twins, cloud computing/edge computing/fog computing, has provided theoretical and technical support for solving the above problems. It has been proven that the eye-catching AI technologies, encompassing unsupervised learning, reinforcement learning, transfer learning, and federal learning, are able to enhance the overall performance of communication network systems. Furthermore, under the dual drive of "big data + digital twins", the corresponding and related design of AI architecture/algorithms/processes and information network architecture/algorithms/processes can constitute the basic technical system of the space-air-ground integrated network for future 6G. "China Communications" is planning to release the feature topic of " Space-Air-Ground Integrated Network with Native Intelligence (NI-SAGIN): Concept，Architecture, Access and Networking " in the first issue of 2022. This topic focuses on the space-air-ground integrated architecture, the formation, evolution, deployment and implementation of network native intelligence, and AI-driven integrated network operation management, including access control/mobile management/connection management/slicing management, etc.

 

Papers describing algorithms, models, prototypes, implementations, tools, and paradigms are welcome. Survey papers or visionary articles indicating future directions from different perspectives are also encouraged. Extended versions of papers published in conferences, symposium, or workshop proceedings may also be submitted.

 

● SDN/NFV-based satellite network architecture and space-ground integration

● Low-orbit constellation air interface technology and networking technology

● Air platform networking, air interface technology and air-ground-sea integration

● Networked intelligent control, management, and service for UAVs

● Space-air-ground integrated network architecture (including access network and core network) and networking technology

● Novel air interface technology of space-air-ground integrated network

● Network native intelligence and intelligent radio technology

● Native intelligence based access control/mobile management/connection management/slicing management technology

● SDN/NFV based space-air-ground integrated network with native intelligent technology (including structure, deployment, management and application, etc.)

● (IoT, Positioning service, etc.) Application oriented intelligent data processing in space-air-ground integrated network

● End-to-end virtualization technology

● Space-air-ground integrated network with intelligent native security

 

Submission Deadline: May 31, 2021

Acceptance Notification (1st round): July 20, 2021

Minor Revision Due: September 1, 2021

Final Decision Due: September 20, 2021

Final Manuscript Due: October 5, 2021

Publication Date: January 15, 2022

 

Zhenyu Xiao, Beihang University, China

Qihui Wu, Nanjing University of Aeronautics and Astronautics, China

Jiajia Liu, Northwestern Polytechnical University, China

Ning Zhang, University of Windsor, Canada

Tao Sun, China Mobile Research Institute, China

 

This feature topic “Space-Air-Ground Integrated Network with Native Intelligence (NI-SAGIN): Concept, Architecture, Access and Networking” invites submissions of original, previously unpublished technical papers and visionary articles exploring the architecture, access, networking and data processing in Space-Air-Ground Integrated Network. All submissions will be anonymously peer reviewed and will be evaluated on the basis of their technical content. Potential topics of interest include, but not limited to areas listed above.

Papers should be submitted in two separate .doc files (preferred) or .pdf files: 1) Main Document (including paper title, abstract, key words, and full text); 2) Title page (including paper title, author affiliation, acknowledgement and any other information related with the authors’ identification) through the Manuscript Central. Please register or login at http://mc03.manuscriptcentral.com/chinacomm, then go to the author center and follow the instructions there. Remember to select “Space-Air-Ground Integrated Network with Native Intelligence (NI-SAGIN): Concept，Architecture, Access and Networking—January Issue, 2022” as your manuscript type when submitting; otherwise, it might be considered as a regular paper.

 

Each submission must be accompanied by the following information:

● an abstract of about 180-250 words

● 3-8 keywords

● original photographs with high-resolution (300 dpi or greater); eps. or tif. format is preferred; sequentially numbered references.

● sequentially numbered references. The basic reference format is: author name, "article name", issue name (italic), vol., no., page, month, year. for example: Y. M. Huang, "Pervateture in wireless heterogeneous…", IEEE Journal on Selected Areas, vol. 27, no. 5, pp 34-50, May, 2009

● brief biographies of authors (50-75 words)

● contact information, including email and mailing addresses