Adaptive RRI Selection Algorithms for Improved Cooperative Awareness in Decentralized NR-V2X

TL;DR

This paper proposes adaptive RRI selection algorithms to enhance cooperative awareness in decentralized NR-V2X networks, addressing the limitations of fixed RRIs under high vehicle density conditions.

Contribution

The study introduces novel adaptive RRI algorithms that improve cooperative awareness and reduce tracking error in dense V2X scenarios compared to traditional fixed RRI methods.

Findings

Adaptive RRI algorithms significantly reduce tracking error in high-density scenarios.

Enhanced cooperative awareness extends vehicle sensing and perception range.

The proposed methods outperform existing fixed RRI approaches in simulation tests.

Abstract

Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error. Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error.