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Ground-Air-Space Networks Relying on Real Flight Data

Research Topics


In support of ubiquitous connectivity, non-terrestrial and terrestrial convergence has already been initiated by the third Generation Partnership Project (3GPP)  for improving the availability and reliability of next-generation wireless networks (NGWNs). Therefore, it is expected to provide seamless connectivity between the home, the airport terminal and the aircraft cabin in NGWNs. In contrast to enhancing a single one of the key performance metrics, most use cases of NGWNs are expected to find all optimal operating points in terms of latency, throughput, energy consumption and so on. 

3D network

Fig. 1: Illustrations of a topological framework of the interconnected space-air-ground network projected onto the vertical plane, which comprises six layers of different altitudes of the infrastructure entities.

  • Single-Objective Optimizations 

Relying on multi-hop communication techniques, aeronautical ad hoc networks (AANETs) seamlessly integrate ground base stations (BSs) and satellites into aircraft communications for enhancing the on-demand connectivity of planes in the air. Our research starts from assessing the performance of the classic shortest-path routing algorithm in the context of the real flight data collected in the North-Atlantic Region. Specifically, in this integrated AANET context we investigate the shortest-path routing problem with the objective of minimizing the total delay of the in-flight connection from the ground BS subject to certain minimum-rate constraints for all selected links in support of low-latency and high-speed services. Inspired by the best-first search and priority queue concepts, we model the problem formulated by a weighted digraph and find the optimal route based on the shortest-path algorithm. 

Related research paper:

J. Cui, D. Liu, J. Zhang, H. Yetgin, S. X. Ng, R. G. Maunder, L. Hanzo,"Minimum-Delay Routing for Integrated Aeronautical Ad Hoc Networks Relying on Real Flight Data in the North-Atlantic Region", in IEEE OJVT, vol. 2, pp. 310-320, 2021.[Full paper]


  • Multi-Objective Optimizations 

Sparked by numerous emerging applications rolled out in next generation wireless networks (NWGNs), more diverse and more complex technological demands than traditional communications have to be conceived. In contrast to enhancing a single one of the key performance metrics, most use cases of NGWNs are expected to find all optimal operating points in terms of latency, throughput, energy consumption and so on.  For meeting the latency and reliability requirements of in-flight connectivity, we formulate a multi-objective multi-hop routing problem in aeronautical ad hoc networks (AANETs) for concurrently optimizing multiple end-to-end performance metrics in terms of the total delay and the throughput. In contrast to single-objective optimization problems that may have a unique optimal solution, the problem formulated is a multi-objective combinatorial optimization problem (MOCOP), which generally has a set of trade-off solutions, called the Pareto optimal set. Due to the discrete structure of the MOCOP formulated, finding the Pareto optimal set becomes excessively complex for large-scale networks. Therefore, we employ a multi-objective evolutionary algorithm (MOEA), namely the classic NSGA-II for generating an approximation of the Pareto optimal set.


Fig. 2: Requirements of KPIs for IMT-2000, IMT-Advance, IMT-2020 and the future networks

Related research paper: 

J. Cui, H. Yetgin, D. Liu, J. Zhang, S. X. Ng and L. Hanzo, "Twin-Component Near-Pareto Routing Optimization for AANETs in the North-Atlantic Region Relying on Real Flight Statistics," in IEEE OJVT, 2021.[Full paper]

J. Cui, S. X. Ng, D. Liu, J. Zhang, A. Nallanathan and L. Hanzo, “Multi-objective optimization for integrated ground-air-space networks,” IEEE VTM, 2021. [Full paper]