QoS-Constrained Resource Pattern Design for V2X-ISAC Systems

2026-10-03

AI Summary

This study addresses the challenges of heterogeneous communication quality and the inherent trade-off between sensing and communication performance caused by channel disparities in V2X integrated sensing and communication (ISAC) systems. To tackle these issues, this work proposes a QoS-constrained resource pattern selection framework. The framework characterizes sensing performance using the Fisher information matrix and introduces a minimum packet reception rate to guarantee communication reliability. Furthermore, an efficient solution algorithm combining greedy search with local swap refinement is designed. Experimental results demonstrate that the proposed method significantly enhances sensing performance while strictly satisfying communication constraints, closely approaching the solutions obtained via exhaustive search and pure sensing-optimal baselines. Ultimately, this approach achieves joint system-level optimization of both sensing and communication capabilities.

Abstract

Integrated sensing and communication (ISAC) has emerged as a promising approach for vehicle-to-everything (V2X) systems by enabling communication and sensing over shared radio resources without additional installation of dedicated sensors. However, candidate resources may experience different communication qualities due to varying channel conditions and resource contention, which should be considered when designing sensing resource patterns. In this letter, we propose a quality-of-service (QoS)-constrained resource pattern selection framework that jointly considers communication reliability and sensing performance. The sensing objective is formulated based on the Fisher information matrix for joint range and velocity estimation, while a minimum packet reception ratio (PRR) is imposed as the communication QoS constraint. To avoid the complexity of exhaustive search, a greedy selection algorithm with one-swap refinement is developed. Simulation results show that the proposed method improves sensing performance over conventional resource patterns while satisfying the PRR requirement and achieves performance close to the exhaustive-search optimum and sensing-only optimum.

Problem

• V2X-ISAC
• Resource Pattern Design
• Quality of Service
• Sensing Performance
• Communication Reliability

Innovation

• Integrated Sensing and Communication (ISAC)
• Resource Pattern Selection
• Fisher Information Matrix
• QoS-Constrained Optimization
• Greedy Algorithm