Full-Frame OFDM-ISAC for Traffic Monitoring in 6G V2X Networks

Abstract

Integrated sensing and communication (ISAC) has emerged as a cornerstone technology for next-generation vehicleto-everything (V2X) networks, offering a spectrally efficient approach to high-resolution environmental awareness. This paper presents an orthogonal frequency division multiplexing (OFDM)-based ISAC imaging framework tailored for real-time traffic monitoring via road side units (RSUs). By exploiting the complete frame structure of OFDM signals, incorporating both pilot symbols and data payloads, we develop a signal processing pipeline that transforms reflected communication waveforms into high-fidelity radar images. Specifically, we derive a closedform expression for sensing performance that accounts for the joint contribution of pilots and random data payloads. Moving beyond classical radar processing, this work bridges the gap between ISAC imaging and intelligent transportation system (ITS) metrics, effectively translating target detection performance into actionable carriageway-level speed and occupancy data. Furthermore, we introduce a dedicated real-time traffic monitoring ISAC simulator platform, which provides an extensive evaluation of imaging performance within dynamic V2X environments. This framework enables the exploration of OFDM-ISAC imaging across diverse traffic scenarios, demonstrating its potential as a scalable solution for future smart infrastructure.