# UAV Swarm-enabled Collaborative Post-disaster Communications in Low Altitude Economy via a Two-stage Optimization Approach

arXiv: https://arxiv.org/abs/2501.05742 · HTML: https://mlsanity.com/paper/2501.05742/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jan 2025.

## Built on by (most cited first, 3 of 3)

- [Diffusion Models for Future Networks and Communications: A Comprehensive Survey](https://mlsanity.com/paper/2508.01586/) (2025)
- [Joint Task Offloading and Resource Allocation in Low-Altitude MEC via Graph Attention Diffusion](https://mlsanity.com/paper/2506.21933/) (2025)
- [Spatiotemporal Continual Federated Learning for Agentic Multi-UAV Edge Networks: Mitigating Catastrophic Forgetting](https://mlsanity.com/paper/2601.21861/) (2026)

## Abstract (arXiv)

The low-altitude economy (LAE) plays an indispensable role in cargo transportation, healthcare, infrastructure inspection, and especially post-disaster communication. Specifically, unmanned aerial vehicles (UAVs), as one of the core technologies of the LAE, can be deployed to provide communication coverage, facilitate data collection, and relay data for trapped users, thereby significantly enhancing the efficiency of post-disaster response efforts. In this paper, we design an efficient and robust UAV-swarm enabled collaborative self-organizing network to facilitate post-disaster communications. Specifically, a ground device transmits data to UAV swarms, which then use collaborative beamforming (CB) technique to form virtual antenna arrays and relay the data to a remote access point (AP) efficiently. Then, we formulate a rescue-oriented post-disaster transmission rate maximization optimization problem (RPTRMOP). Then, we propose a two-stage optimization approach to address it. In the first stage, the optimal traffic routing and the theoretical upper bound on the transmission rate of the network are derived. In the second stage, we transform the formulated RPTRMOP into a variant named V-RPTRMOP, and a diffusion model-enabled particle swarm optimization (DM-PSO) algorithm is proposed to deal with the V-RPTRMOP. Simulation results show the effectiveness of the proposed two-stage optimization approach in improving the transmission rate of the constructed network, which demonstrates the great potential for post-disaster communications. Moreover, the robustness of the constructed network is also validated via evaluating the impact of two unexpected situations on the system transmission rate.