Extreme Value Theory-enhanced Radio Maps for Handovers in Ultra-reliable Communications

Efficient handover (HO) strategies are essential for maintaining the stringent performance requirements of ultra-reliable communication (URC) systems. This work introduces a novel HO framework designed from a physical-layer perspective, where the decision-making process focuses on determining the optimal time and location for performing HOs. Leveraging extreme value theory (EVT) and statistical radio maps, the proposed method predicts signal behaviour and enables efficient resource allocation. The framework ensures seamless HOs and improved system performance by facilitating effective resource transitions and coordination across spatial locations while incorporating mechanisms to mitigate the ping-pong effect. Comparative evaluations demonstrate that this strategy provides superior service availability and energy efficiency than traditional HO mechanisms, highlighting its effectiveness in URC environments.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-01-01
DOI
https://doi.org/10.1109/tvt.2025.3617346
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
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article

Extreme Value Theory-enhanced Radio Maps for Handovers in Ultra-reliable Communications

Onel L. Alcaraz López, Hirley Alves, Dian Echevarría Pérez
IEEE Transactions on Vehicular Technology
Advanced MIMO Systems Optimization
article

Extreme Value Theory-enhanced Radio Maps for Handovers in Ultra-reliable Communications

Onel L. Alcaraz López, Hirley Alves, Dian Echevarría Pérez
article en

Abstract

Efficient handover (HO) strategies are essential for maintaining the stringent performance requirements of ultra-reliable communication (URC) systems. This work introduces a novel HO framework designed from a physical-layer perspective, where the decision-making process focuses on determining the optimal time and location for performing HOs. Leveraging extreme value theory (EVT) and statistical radio maps, the proposed method predicts signal behaviour and enables efficient resource allocation. The framework ensures seamless HOs and improved system performance by facilitating effective resource transitions and coordination across spatial locations while incorporating mechanisms to mitigate the ping-pong effect. Comparative evaluations demonstrate that this strategy provides superior service availability and energy efficiency than traditional HO mechanisms, highlighting its effectiveness in URC environments.

IEEE Transactions on Vehicular Technology
University of Oulu (FI)
Openalex Percentile: Top 73%
Advanced MIMO Systems Optimization
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