English

Fluid Aerial Networks: UAV Rotation for Inter-Cell Interference Mitigation

Networking and Internet Architecture 2025-07-03 v1 Signal Processing

Abstract

With the rapid development of aerial infrastructure, unmanned aerial vehicles (UAVs) that function as aerial base stations (ABSs) extend terrestrial network services into the sky, enabling on-demand connectivity and enhancing emergency communication capabilities in cellular networks by leveraging the flexibility and mobility of UAVs. In such a UAV-assisted network, this paper investigates position-based beamforming between ABSs and ground users (GUs). To mitigate inter-cell interference, we propose a novel fluid aerial network that leverages ABS rotation to increase multi-cell capacity and overall network efficiency. Specifically, considering the line-of-sight channel model, the spatial beamforming weights are determined by the orientation angles of the GUs. In this direction, we examine the beamforming gain of a two-dimensional multiple-input multiple-output (MIMO) array at various ground positions, revealing that ABS rotation significantly affects multi-user channel correlation and inter-cell interference. Based on these findings, we propose an alternative low-complexity algorithm to design the optimal rotation angle for ABSs, aiming to reduce inter-cell interference and thus maximize the sum rate of multi-cell systems. In simulations, exhaustive search serves as a benchmark to validate the optimization performance of the proposed sequential ABS rotation scheme. Moreover, simulation results demonstrate that, in interference-limited regions, the proposed ABS rotation paradigm can significantly reduce inter-cell interference in terrestrial networks and improve the multi-cell sum rate by approximately 10\% compared to fixed-direction ABSs without rotation.

Keywords

Cite

@article{arxiv.2507.01289,
  title  = {Fluid Aerial Networks: UAV Rotation for Inter-Cell Interference Mitigation},
  author = {Enzhi Zhou and Yue Xiao and Ziyue Liu and Sotiris A. Tegos and Panagiotis D. Diamantoulakis and George K. Karagiannidis},
  journal= {arXiv preprint arXiv:2507.01289},
  year   = {2025}
}
R2 v1 2026-07-01T03:42:32.143Z