Intelligent Blockage Prediction and Proactive Handover for Seamless Connectivity in Vision-Aided 5G/6G UDNs
Mohammad Al-Quraan, Ahsan Khan, Lina Mohjazi, Anthony Centeno, Ahmed, Zoha, Muhammad Ali Imran

TL;DR
This paper presents a novel vision-aided mechanism for predicting blockages and performing proactive handovers in ultra-dense 5G/6G networks, significantly improving user connectivity and QoE in urban environments.
Contribution
It introduces a new blockage prediction and proactive handover method utilizing computer vision and surveillance data, enhancing mobility management in high-frequency UDNs.
Findings
Achieves 40% improvement in maintaining user connectivity.
Effectively predicts blockages using computer vision.
Reduces handover failures and improves QoE.
Abstract
The upsurge in wireless devices and real-time service demands force the move to a higher frequency spectrum. Millimetre-wave (mmWave) and terahertz (THz) bands combined with the beamforming technology offer significant performance enhancements for ultra-dense networks (UDNs). Unfortunately, shrinking cell coverage and severe penetration loss experienced at higher spectrum render mobility management a critical issue in UDNs, especially optimizing beam blockages and frequent handover (HO). Mobility management challenges have become prevalent in city centres and urban areas. To address this, we propose a novel mechanism driven by exploiting wireless signals and on-road surveillance systems to intelligently predict possible blockages in advance and perform timely HO. This paper employs computer vision (CV) to determine obstacles and users' location and speed. In addition, this study…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Advanced MIMO Systems Optimization · Telecommunications and Broadcasting Technologies
Methodstravel james
