Current maritime communications mainly rely on satellites having meager
transmission resources, hence suffering from poorer performance than modern
terrestrial wireless networks. With the growth of transcontinental air traffic,
the promising concept of aeronautical ad hoc networking relying on commercial
passenger airplanes is potentially capable of enhancing satellite-based
maritime communications via air-to-ground and multi-hop air-to-air links. In
this article, we conceive space-air-ground integrated networks (SAGINs) for
supporting ubiquitous maritime communications, where the low-earth-orbit
satellite constellations, passenger airplanes, terrestrial base stations,
ships, respectively, serve as the space-, air-, ground- and sea-layer. To meet
heterogeneous service requirements, and accommodate the time-varying and
self-organizing nature of SAGINs, we propose a deep learning (DL) aided
multi-objective routing algorithm, which exploits the quasi-predictable network
topology and operates in a distributed manner. Our simulation results based on
real satellite, flight, and shipping data in the North Atlantic region show
that the integrated network enhances the coverage quality by reducing the
end-to-end (E2E) delay and by boosting the E2E throughput as well as improving
the path-lifetime. The results demonstrate that our DL-aided multi-objective
routing algorithm is capable of achieving near Pareto-optimal performance.

本文提出了一种空 - 空 - 地 - 海一体化网络，通过深度学习算法帮助多目标路由，利用商用客机来增强以卫星为基础的海上通信，以降低端到端延迟，提高通信吞吐量并改善路径寿命，达到近似 Pareto 最优的性能

基于真实卫星、飞行和航运数据的深度学习辅助空中 - 地面 - 空运综合网络路由

Deep Learning Aided Routing for Space-Air-Ground Integrated Networks  Relying on Real Satellite, Flight, and Shipping Data

The engineering vision of relying on the ``smart sky" for supporting air
traffic and the ``Internet above the clouds" for in-flight entertainment has
become imperative for the future aircraft industry. Aeronautical ad hoc
Networking (AANET) constitutes a compelling concept for providing broadband
communications above clouds by extending the coverage of Air-to-Ground (A2G)
networks to oceanic and remote airspace via autonomous and self-configured
wireless networking amongst commercial passenger airplanes. The AANET concept
may be viewed as a new member of the family of Mobile ad hoc Networks (MANETs)
in action above the clouds. However, AANETs have more dynamic topologies,
larger and more variable geographical network size, stricter security
requirements and more hostile transmission conditions. These specific
characteristics lead to more grave challenges in aircraft mobility modeling,
aeronautical channel modeling and interference mitigation as well as in network
scheduling and routing. This paper provides an overview of AANET solutions by
characterizing the associated scenarios, requirements and challenges.
Explicitly, the research addressing the key techniques of AANETs, such as their
mobility models, network scheduling and routing, security and interference are
reviewed. Furthermore, we also identify the remaining challenges associated
with developing AANETs and present their prospective solutions as well as open
issues. The design framework of AANETs and the key technical issues are
investigated along with some recent research results. Furthermore, a range of
performance metrics optimized in designing AANETs and a number of
representative multi-objective optimization algorithms are outlined.

本篇论文概述了在机载通信领域中，利用航空自组网提供广域网通信的方法和技术，介绍了这种新型航空自组网的关键技术，包括移动模型、网络调度和路由、安全和干扰等，并指出了仍需要解决的问题和展望。