IEEE 802.11ad-based Radar: An Approach to Joint Vehicular Communication-Radar System

Millimeter-wave (mmWave) radar is widely used in vehicles for applications such as adaptive cruise control and collision avoidance. In this paper, we propose an IEEE 802.11ad-based radar for long-range radar (LRR) applications at the 60 GHz unlicensed band. We exploit the preamble of a single-carrier (SC) physical layer (PHY) frame, which consists of Golay complementary sequences with good correlation properties, as a radar waveform. This system enables a joint waveform for automotive radar and a potential mmWave vehicular communication system based on IEEE 802.11ad, allowing hardware reuse. To formulate an integrated framework of vehicle-to-vehicle (V2V) communication and LRR based on a mmWave consumer wireless local area network (WLAN) standard, we make typical assumptions for LRR applications and incorporate the full duplex radar assumption due to the possibility of sufficient isolation and self-interference cancellation. We develop singleand multi-frame radar receiver algorithms for target detection as well as range and velocity estimation within a coherent processing interval. Our proposed radar processing algorithms leverage channel estimation and time-frequency synchronization techniques used in a conventional IEEE 802.11ad receiver with minimal modifications. Analysis and simulations show that in a single target scenario, a Gbps data rate is achieved simultaneously with cm-level range accuracy and cm/s-level velocity accuracy. The target vehicle is detected with a high probability of detection (>99.9%) at a low false alarm of 10−6 for an equivalent isotropically radiated power (EIRP) of 43 dBm up to a vehicle separation distance of 200 m. Preeti Kumari and Robert W. Heath Jr. are with the Wireless Networking and Communications Group, the University of Texas at Austin, TX 78712-1687, USA (e-mail: {preeti kumari, rheath}@utexas.edu). J. Choi is with the Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea 37673 (e-mail:[email protected]). Nuria González-Prelcic is with the Department of Signal Theory and Communications, Universidade de Vigo, Vigo, Spain 36310 (email: [email protected]) This research was partially supported by the U.S. Department of Transportation through the Data-Supported Transportation Operations and Planning (D-STOP) Tier 1 University Transportation Center and by the Texas Department of Transportation under Project 0-6877 entitled “Communications and Radar-Supported Transportation Operations and Planning (CAR-STOP)”. This work was also supported by a gift from National Instruments. ar X iv :1 70 2. 05 83 3v 1 [ cs .I T ] 2 0 Fe b 20 17