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Related Experiment Video

Updated: Jul 17, 2026

Computer Vision-Based Biomass Estimation for Invasive Plants

Computer Vision-Based Biomass Estimation for Invasive Plants

Published on: February 9, 2024

Modeling and analysis of UAV-Assisted sparse ground networks.

Huakui Sun¹, Yang Zhou²

¹School of Airspace Science and Engineering, Shandong University, Shandong, China.

|July 15, 2026

Summary

The proposed Air-and-Ground Cooperative Network (AGCN) enhances cellular coverage in remote areas. Optimal user connection bias settings are identified to maximize network performance and load balance aerial and ground base stations.

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Last Updated: Jul 17, 2026

Computer Vision-Based Biomass Estimation for Invasive Plants

Computer Vision-Based Biomass Estimation for Invasive Plants

Published on: February 9, 2024

Area of Science:

Telecommunications Engineering
Wireless Communication Systems
Network Architecture

Background:

Traditional ground cellular networks struggle with seamless wide-area coverage, especially in remote regions.
Increasing communication demands necessitate innovative solutions beyond ground-based infrastructure.

Purpose of the Study:

To propose and analyze an Air-and-Ground Cooperative Network (AGCN) architecture for enhanced network coverage.
To investigate the integration of Cell Range Expansion (CRE) technology for load balancing.
To optimize user access strategies for improved network performance.

Main Methods:

Stochastic geometry theory was employed to analyze user access probability and distance distribution.
Analytical formulas for network throughput and traversal rate were derived.
The impact of user connection bias on network performance within the CRE framework was analyzed.

Main Results:

The AGCN architecture significantly enhances network coverage performance.
User connection bias was found to be a critical factor in coordinating coverage and load balancing.
Simulation results validated the theoretical analysis and demonstrated the AGCN's effectiveness.

Conclusions:

The AGCN architecture offers a viable solution for expanding cellular network coverage, particularly in underserved areas.
An optimal user connection bias exists for maximizing overall network performance.
The findings provide valuable insights for designing future integrated air-and-ground communication networks.