Current Initiatives

  • Millimeter Wave Vehicular Beam Prediction with Situational Awareness

    The key to a feasible mmWave vehicular beam configuration method is the ubiquitous side information in vehicular systems, which makes everything connected and equips the vehicles with situational awareness.

  • Experimental investigation of non-line-of-sight millimeter wave V2V channels

    In the vehicular environment, link blockage by neighboring vehicles can happen frequency and, depending on their relative speeds, blockage can last for multiple seconds. We are investigating the utility of reflection paths off vehicles through mmWave channel measurements.

  • Side-Information Assisted Beam Training and Tracking for MmWave V2V Communication

    The crucial challenge of mmWave vehicular communication lies in the conflict between the high overhead of initial access and the low latency requirement of highly mobile vehicles. We are solving this problem by exploiting side-information (provided by IEEE 802.11p-based DSRC) to perform position-based beam training and motion-based beam tracking algorithm using IEEE 802.11ad protocol as a starting point.

  • Simultaneous multi-node beamforming for mmWave V2V network

    Developing methods for beam training in vehicle-to-vehicle millimeter wave networks. We are developing an optimal policy for the beamforming that considers the location informations and finds the optimal beams for multiple nodes simultaneously in minimum number of iterations.

  • Joint radar and communication with low resolution

    Exploiting wide bandwidths at millimeter wave for radar and communication by reducing the resolution of the data converters.

  • Low-Resolution Transceiver Design for 5G New Radio and Beyond

    Decreasing DAC and ADC resolution reduces power consumption, enabling wide bandwidths in millimeter wave and the use of large digital arrays in massive MIMO. New theory and algorithms are needed to embrace ultra low resolution.

  • 5G-Enhanced ADAS

    Using 5G to supercharge advanced driver assistance systems (ADAS). The main idea is to leverage high data rate and low latency characteristics to improve situational awareness.

  • Cooperative Mapping for Automated Vehicles

    Making and updating accurate prior maps using a specialized vehicle fleet is expensive and cumbersome. A key enabler for large-scale up-to-date maps will be enlisting the help of the very vehicles who need the map—consumer vehicles—to build and update the map.

  • Using Cellular Infrastructure in Transportation Applications

    ​Millimeter-wave joint vehicular communication and radar would allow intelligent transportation systems to simultaneously reap the benefits of autonomously sensing the driving environment...

  • Automotive Radar Using WiFi and DSRC Signals

    Recent mandates for automation in vehicular transportation safety have increased demand for radar applications such as forward collision detection and avoidance.

  • Position-Aided Beam Alignment for mmWave Systems

    ​Beam alignment of arrays at this scale is challenging due to the overhead in determining the optimal transmit and receive beams. Existing beam alignment schemes proposed for mmWave applications are largely based on beam sweeping...


    The majority of current collision detection systems use radars, lasers, or cameras. The goal of this project is to demonstrate that systems that rely solely on radar are not as effective as systems with both radar and dedicated short-range communications (DSRC).

  • Automated Intersections Without Traffic Lights (AIM)

    This project "AIM"s to create a scalable, safe, and efficient multi-agent framework for managing autonomous vehicles at intersections.

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