Mobility scenarios involving short contact times pose a challenge for high bandwidth data transfer between autonomous vehicles and roadside base stations (BS). Millimeter wave bands are a viable solution as they offer enormous bandwidth in the 60GHz band with several Gbps data transfer rates. However, beamforming is used as a default mode in this band, which requires accurate and continuous alignment under relative motion. We propose a method in which an off-the-shelf IEEE 802.11ad WiFi router is configured to serve as the BS as well as a radar exploiting special structure of 802.11ad preamble. We embed the radar functionality within standards-compliant operations that do not modify the core structure of the frames beyond what is defined by the 802.11ad protocol. This not only reduces the beam training time, but also ensures scalability with increasing vehicular traffic because radar allows accurate ranging of up to 0.1m at distances up to 200m. We further analyze the ensuing cost-benefit trade-off between the time allotted to the proposed in-band radar and communication modes. Our results reveal 83% reduction on the overhead incurred during the beam training achieved for a specific simulated vehicular scenario over the classical 802.11ad operation.

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In this work, a new Time Difference of Arrival (TDoA) scheme for distance measurement based on Optical Camera Communication (OCC) systems is proposed. It relies on the use of optical pulses instead of radio-frequency signals as the time reference triggers, and the introduction of a rolling shutter camera, whose characteristics allows substituting the timer modules used in conventional TDoA techniques by image processing of the illuminated area in the picture. This processing on the camera’s images provides time measurements and implies and specific analysis, which is presented in this work. The system performance and properties, such as resolution and range, mainly depends on the camera characteristics, such as the frames capture rate and the image quality. This new technique is suitable to be implemented in smartphones or other Commercial Off-The-Shelf (COTS) devices equipped with a camera and speakers.

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