LAUSR

Long-range backscatter communication has the potential to provide enough time and space for vehicles to detect traffic information, which is an attractive solution for Vehicle-to-Infrastructure (V2I) communication. However, existing backscatter studies either require the tag to be close to the carrier source (ambient backscatter) or have poor receiver sensitivity (RFID), making it challenging to satisfy the high range requirements of V2I communication. In this article, we develop AllSpark to investigate the feasibility of long-range communication enabling backscatter to be applied to V2I. Specifically, to increase RSS to compensate for the enormous dual-path loss in backscatter systems, we first redesign the tag’s radio frequency (RF) front-end to amplify the incident signals, and then we design high-gain directional antennas for the tag and reader. Second, we present EC-Net, an end-to-end demodulator that selectively enhances signal features (denoising) and is tuned to lower classification (demodulation) error to maximize demodulation accuracy. Furthermore, we adopt convolutional encoding for tag data and use the output probability of EC-Net to design an effective soft decoder to resist occasional interference and noise, improving communication robustness. Our prototype and experiments outdoors verify the effectiveness of AllSpark which can provide a communication range of 700 m. Even in a moving scene, it can achieve a communication range of 600 m, demonstrating that AllSpark has the potential to be applied for autonomous driving and low-flying drones to detect traffic conditions.