Hyper-Accurate Cooperative Perception Routing for Millimeter Wave V2X Communications in Dense Urban Environments

**Abstract:** This paper introduces a novel cooperative perception routing (CPR) framework optimized for millimeter wave (mmWave) Vehicle-to-Everything (V2X) communications within dense urban environments. Addressing the limitations of traditional routing protocols in rapidly changing urban landscapes and the inherent path loss challenges of mmWave frequencies, our system leverages a hierarchical prediction network and dynamic beam steering optimization to ensure ultra-reliable low-latency communication (URLLC) for critical safety applications. The proposed CPR mechanism enhances signal reliability by intelligently routing data through a network of connected vehicles and road-side units (RSUs) predicted to exhibit the most favorable communication links based on real-time environmental data and anticipated vehicle trajectories. This approach achieves a 2.5x improvement in message delivery rate compared to baseline routing protocols under complex urban conditions, while maintaining URLLC requirements for advanced driver-assistance systems (ADAS) and autonomous driving functionalities.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-04
DOI
https://doi.org/10.5281/zenodo.17053619
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Hyper-Accurate Cooperative Perception Routing for Millimeter Wave V2X Communications in Dense Urban Environments

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Hyper-Accurate Cooperative Perception Routing for Millimeter Wave V2X Communications in Dense Urban Environments

article en

Abstract

**Abstract:** This paper introduces a novel cooperative perception routing (CPR) framework optimized for millimeter wave (mmWave) Vehicle-to-Everything (V2X) communications within dense urban environments. Addressing the limitations of traditional routing protocols in rapidly changing urban landscapes and the inherent path loss challenges of mmWave frequencies, our system leverages a hierarchical prediction network and dynamic beam steering optimization to ensure ultra-reliable low-latency communication (URLLC) for critical safety applications. The proposed CPR mechanism enhances signal reliability by intelligently routing data through a network of connected vehicles and road-side units (RSUs) predicted to exhibit the most favorable communication links based on real-time environmental data and anticipated vehicle trajectories. This approach achieves a 2.5x improvement in message delivery rate compared to baseline routing protocols under complex urban conditions, while maintaining URLLC requirements for advanced driver-assistance systems (ADAS) and autonomous driving functionalities.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Sustainable cities and communities
Openalex Percentile: Top 54%
Geochemistry and Geologic Mapping
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