Performance Analysis of Millimeter Wave Radar Waveforms for Integrated Sensing and Communication

TL;DR

This paper compares various waveforms for integrated sensing and communication in transportation, showing IEEE 802.11ad outperforms traditional radar waveforms in target detection and analyzing hardware implementation complexities.

Contribution

It provides a comparative analysis of traditional radar and communication waveforms for ISAC, highlighting the superior performance of IEEE 802.11ad and evaluating real-world hardware implementation aspects.

Findings

IEEE 802.11ad outperforms PMCW and FMCW radars in target detection.

FMCW radar has poorer response to mobile targets compared to PMCW.

Hardware-software co-design and fixed-point analysis assess implementation complexity.

Abstract

Next-generation intelligent transportation systems require both sensing and communication between road users. However, deploying separate radars and communication devices involves the allocation of individual frequency bands and hardware platforms. Integrated sensing and communication (ISAC) offers a robust solution to the challenges of spectral congestion by utilizing a shared waveform, hardware, and spectrum for both localization of mobile users and communication. Various waveforms, including phase-modulated continuous waves (PMCW) and frequency-modulated continuous waves (FMCW), have been explored for target localization using traditional radar. On the other hand, new protocols such as the IEEE 802.11ad have been proposed to support wideband communication between vehicles. This paper compares both traditional radar and communication candidate waveforms for ISAC to detect single-point and extended targets. We show that the response of FMCW to mobile targets is poorer than that of PMCW. However, the IEEE 802.11ad radar outperforms PMCW radar and FMCW radar. Additionally, the radar signal processing algorithms are implemented on Zynq system-on-chip through hardware-software co-design and fixed-point analysis to evaluate their computational complexity in real-world implementations.