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Multi-Tier Non-Terrestrial Networking for Disaster Communications: A Layered Clustering Approach

Metin Ozturk, Berk Çiloğlu, Görkem Berkay Koç, Halim Yanikomeroglu

TL;DR

This work tackles the challenge of maintaining communications in disaster scenarios where terrestrial networks are compromised. It proposes a three-tier non-terrestrial network combining ground UEs, UAV-BS RANs, and a HAPS-SMBS backhaul, integrated with a two-layer clustering framework to optimize UAV placement and backhaul topology. The authors introduce an energy-centric modeling approach, including the energy score $E_s = \lambda d$ and the backhaul-focused metric $E_p = \sum_{j=1}^{n-1} (\lambda_j \overline{d_{j,e}} + \lambda_k d_{j,H})$, and compare the proposed DLC-AHN topology against SLC and CUP benchmarks using energy-based evaluations. Results show that DLC-AHN substantially lowers energy expenditure and extends network lifespan across various user densities and UAV counts, by channeling backhaul through a single or limited set of H-UAVs connected to the HAPS-SMBS. These findings suggest a practical, scalable approach for resilient disaster communications with rapid deployment and improved operational resilience.

Abstract

It is crucial to deploy temporary non-terrestrial networks (NTN) in disaster situations where terrestrial networks are no longer operable. Deploying uncrewed aerial vehicle base stations (UAV-BSs) can provide a radio access network (RAN); however, the backhaul link may also be damaged and unserviceable in such disaster conditions. In this regard, high-altitude platform stations (HAPS) spark attention as they can be deployed as super macro base stations (SMBS) and data centers. Therefore, in this study, we investigate a three-layer heterogeneous network with different topologies to prolong the lifespan of the temporary network by using UAV-BSs for RAN services and HAPS-SMBS as a backhaul. Furthermore, a two-layer clustering algorithm is proposed to handle the UAV-BS ad-hoc networking effectively.

Multi-Tier Non-Terrestrial Networking for Disaster Communications: A Layered Clustering Approach

TL;DR

This work tackles the challenge of maintaining communications in disaster scenarios where terrestrial networks are compromised. It proposes a three-tier non-terrestrial network combining ground UEs, UAV-BS RANs, and a HAPS-SMBS backhaul, integrated with a two-layer clustering framework to optimize UAV placement and backhaul topology. The authors introduce an energy-centric modeling approach, including the energy score and the backhaul-focused metric , and compare the proposed DLC-AHN topology against SLC and CUP benchmarks using energy-based evaluations. Results show that DLC-AHN substantially lowers energy expenditure and extends network lifespan across various user densities and UAV counts, by channeling backhaul through a single or limited set of H-UAVs connected to the HAPS-SMBS. These findings suggest a practical, scalable approach for resilient disaster communications with rapid deployment and improved operational resilience.

Abstract

It is crucial to deploy temporary non-terrestrial networks (NTN) in disaster situations where terrestrial networks are no longer operable. Deploying uncrewed aerial vehicle base stations (UAV-BSs) can provide a radio access network (RAN); however, the backhaul link may also be damaged and unserviceable in such disaster conditions. In this regard, high-altitude platform stations (HAPS) spark attention as they can be deployed as super macro base stations (SMBS) and data centers. Therefore, in this study, we investigate a three-layer heterogeneous network with different topologies to prolong the lifespan of the temporary network by using UAV-BSs for RAN services and HAPS-SMBS as a backhaul. Furthermore, a two-layer clustering algorithm is proposed to handle the UAV-BS ad-hoc networking effectively.
Paper Structure (9 sections, 3 equations, 4 figures)

This paper contains 9 sections, 3 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Network Model
  4. Energy Consumption Model
  5. Multi-Tier Non-Terrestrial Networking for Disaster Communications
  6. Performance Evaluation
  7. Benchmarking
  8. Results and Discussions
  9. Conclusion

Figures (4)

  • Figure 1: A city model is formed during a disaster, infrastructures have collapsed and communication is provided by UAVs, HAPS is backhauling the UAVs, and UEs are clustered in places such as gathering areas.
  • Figure 2: Energy score with respect to the user density.
  • Figure 3: Energy score for varying number of $n$ in the first-layer clustering.
  • Figure 4: Energy score for different $k$ values in the second-layer clustering.