A Millimeter Wave-Based Sensor Data Broadcasting Scheme for Vehicular Communications

In this study, we propose a method to identify the type of target and simultaneously determine its moving direction in a millimeter-wave radar system. First, using a frequency-modulated continuous wave (FMCW) radar sensor with the center frequency of 62 GHz, radar sensor data for a pedestrian, a cyclist, and a car are obtained in the test field. Then, a You Only Look Once (YOLO)-based network is trained with the sensor data to perform simultaneous target classification and moving direction estimation. To generate input data suitable for the deep learning-based classifier, a method of converting the radar detection result into an image form is also proposed. With the proposed method, we can identify the type of each target and its direction of movement with an accuracy of over 95%. Moreover, the pre-trained classifier shows an identification accuracy of 85% even for newly acquired data that have not been used for training.

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Millimeter Wave Spatial Channel Characterization for Vehicular Communications

Proceedings ◽

10.3390/ecsa-6-06562 ◽

2019 ◽

Vol 42 (1) ◽

pp. 64 ◽

Cited By ~ 2

Author(s):

Fidel Rodríguez-Corbo ◽

Leyre Azpilicueta ◽

Mikel Celaya-Echarri ◽

Peio López-Iturri ◽

Imanol Picallo ◽

...

Keyword(s):

Millimeter Wave ◽

Autonomous Vehicles ◽

Communication Systems ◽

Vehicular Networks ◽

Small Scale ◽

Vehicular Communications ◽

Next Generation ◽

Vehicular Communication ◽

High Definition ◽

High Data

With the growing demand of vehicle-mounted sensors over the last years, the amount of critical data communications has increased significantly. Developing applications such as autonomous vehicles, drones or real-time high-definition entertainment requires high data-rates in the order of multiple Gbps. In the next generation of vehicle-to-everything (V2X) networks, a wider bandwidth will be needed, as well as more precise localization capabilities and lower transmission latencies than current vehicular communication systems due to safety application requirements; 5G millimeter wave (mmWave) technology is envisioned to be the key factor in the development of this next generation of vehicular communications. However, the implementation of mmWave links arises with difficulties due to blocking effects between mmWave transceivers, as well as different channel impairments for these high frequency bands. In this work, the mmWave channel propagation characterization for V2X communications has been performed by means of a deterministic in-house 3D ray launching simulation technique. A complex heterogeneous urban scenario has been modeled to analyze the different propagation phenomena of multiple mmWave V2X links. Results for large and small-scale propagation effects are obtained for line-of-sight (LOS) and non-LOS (NLOS) trajectories, enabling inter-data vehicular comparison. These analyzed results and the proposed methodology can aid in an adequate design and implementation of next generation vehicular networks.

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