# Cross-field SNR Analysis and Tensor Channel Estimation for Multi-UAV Near-field Communications

arXiv: https://arxiv.org/abs/2509.06967 · HTML: https://mlsanity.com/paper/2509.06967/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 40 references that are in the map.
- First posted on arXiv 23 Aug 2025.

## Builds on (most cited first, 15 of 15)

- [Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond](https://mlsanity.com/paper/2108.07165/) (2021)
- [On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds](https://mlsanity.com/paper/2302.14536/) (2023)
- [A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications](https://mlsanity.com/paper/2307.07340/) (2023)
- [Multi-objective Aerial Collaborative Secure Communication Optimization via Generative Diffusion Model-enabled Deep Reinforcement Learning](https://mlsanity.com/paper/2407.08914/) (2024)
- [A Tutorial on Near-Field XL-MIMO Communications Towards 6G](https://mlsanity.com/paper/2310.11044/) (2023)
- [UAV-enabled Collaborative Beamforming via Multi-Agent Deep Reinforcement Learning](https://mlsanity.com/paper/2404.07453/) (2024)
- [Near-Field Wideband Beamforming for Extremely Large Antenna Arrays](https://mlsanity.com/paper/2109.10054/) (2021)
- [Near-Field Channel Estimation for Extremely Large-Scale Reconfigurable Intelligent Surface (XL-RIS)-Aided Wideband mmWave Systems](https://mlsanity.com/paper/2304.00440/) (2023)
- [An Overview on Integrated Localization and Communication Towards 6G](https://mlsanity.com/paper/2006.01535/) (2020)
- [Hybrid Spherical- and Planar-Wave Channel Modeling and Estimation for Terahertz Integrated UM-MIMO and IRS Systems](https://mlsanity.com/paper/2205.13113/) (2022)
- [How Does Performance Scale with Antenna Number for Extremely Large-Scale MIMO?](https://mlsanity.com/paper/2010.16232/) (2020)
- [Jittering Effects Analysis and Beam Training Design for UAV Millimeter Wave Communications](https://mlsanity.com/paper/2104.05872/) (2021)
- [Mixed Near- and Far-Field Communications for Extremely Large-Scale Array: An Interference Perspective](https://mlsanity.com/paper/2301.07277/) (2023)
- [Performance Bounds for Near-Field Localization with Widely-Spaced Multi-Subarray mmWave/THz MIMO](https://mlsanity.com/paper/2309.05944/) (2023)
- [Near-Field Channel Estimation for Extremely Large-Scale Terahertz Communications](https://mlsanity.com/paper/2406.05452/) (2024)

## Abstract (arXiv)

Extremely large antenna array (ELAA) is key to enhancing spectral efficiency in 6G networks. Leveraging the distributed nature of multi-unmanned aerial vehicle (UAV) systems enables the formation of distributed ELAA, which often operate in the near-field region with spatial sparsity, rendering the conventional far-field plane wave assumption invalid. This paper investigates channel estimation for distributed near-field multi-UAV communication systems. We first derive closed-form signal-to-noise ratio (SNR) expressions under the plane wave model (PWM), spherical wave model (SWM), and a hybrid spherical-plane wave model (HSPWM), also referred to as the cross-field model, within a distributed uniform planar array (UPA) scenario. The analysis shows that HSPWM achieves a good balance between modeling accuracy and analytical tractability. Based on this, we propose two channel estimation algorithms: the spherical-domain orthogonal matching pursuit (SD-OMP) and the tensor-OMP. The SD-OMP generalizes the polar domain to jointly consider elevation, azimuth, and range. Under the HSPWM, the channel is naturally formulated as a tensor, enabling the use of tensor-OMP. Simulation results demonstrate that tensor-OMP achieves normalized mean square error (NMSE) performance comparable to SD-OMP, while offering reduced computational complexity and improved scalability.