Computer vision-based location-aware antenna system for 5G applications
Year: 2025
Type: article
Abstract: The Location-aware communication system is critical in addressing the key challenges in 5G and beyond. The system improves the accuracy and reliability of the communication system by adapting the radiation pattern and beam direction of the base station antenna to the estimated direction of the receiver. This article proposes a computer vision-based location-tracking antenna system that integrates computer vision technology with antenna systems to track the real-time position of potential channel users, terminals or people. The proposed machine learning-based computer vision algorithm analyses the visual data obtained using the YOLO algorithm with an optimisation technique to extract the positional coordinates to rotate the antenna system mounted on a rotating assembly. The beam generated by the antenna is pointed in the desired direction, as determined by the algorithm. The designed Multi-Input, Multi-Output (MIMO) antenna operates at 3.7GHz and 5.45GHz dual bands. The performance parameters of MIMO antennas, including isolation, Envelope Correlation Coefficient (ECC), Total Active Reflection Coefficient (TARC), and Mean Effective Gain (MEG), are all within the specified range. This compliance indicates that the antennas can provide excellent diversity performance, which enhances signal reliability and overall communication quality. The proposed system significantly enhances wireless communication by effectively reducing interference, improving signal quality, and extending coverage range. These improvements contribute to a more reliable and efficient communication experience.
Language: English
Topic: Antenna Design and Analysis
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4409918983