Takaya Yamazato

Qiming Lu, Shan Lu, Takaya Yamazato

Conventional communication systems are mainly designed to reduce error rates and increase transmission rates, and therefore usually provide uniform protection to all transmitted messages. However, in intent-oriented applications, different messages may have different semantic meanings and importance levels, requiring different levels of reliability. This paper proposes a layered construction of message-level unequal error protection (UEP) codes for short-blocklength communication. Instead of appending an explicit protection tag to each codeword, the proposed method embeds the protection structure directly into the Hamming-distance structure of the codebook. By assigning larger minimum intra-level distances to higher-importance message groups and imposing suitable inter-level distance constraints, the proposed codebook provides differentiated error-correction capabilities while enabling reliable importance-level classification at the receiver. Theoretical conditions for correct group classification are derived, and simulations over AWGN and VLC-ISI channels show that the proposed scheme improves BER performance and group classification accuracy compared with a tag-based ECC baseline.

Ryota Soga, Tsukasa Shimizu, Shintaro Shiba et al.

Event cameras offer high temporal resolution, low latency, and wide dynamic range, making them promising receivers for visible light communication (VLC) in vehicle-to-everything (V2X) applications. This work presents an event-camera-based VLC system addressing three key challenges: bandwidth saturation, multi-transmitter reception, and latency characterization. We adopt a positive-event-only mode and design a protocol that suppresses event generation while maintaining communication distance and a wide field of view. We also propose a method to identify multiple transmitters and demonstrate simultaneous reception from up to three LEDs. Finally, we evaluate end-to-end latency in real vehicular scenarios and show that the system meets cooperative perception requirements. These results demonstrate that event-camera-based VLC is a feasible complement to existing V2X technologies (e.g., RF).

Tianhao Shi, Shan Lu, Takaya Yamazato

High-density LED arrays enable high-speed transmission in image-sensor-based visible-light communication (VLC) systems. However, when optical spots become blurred and spatially overlapped due to focal shift, resolution limitations, or interference, severe inter-symbol interference (ISI) occurs, significantly degrading decoding performance. Furthermore, radial distortion introduces geometric deformation of the LED grid, while vignetting leads to incomplete and asymmetric spot shapes at the periphery, both of which further hinder reliable signal detection. Existing methods mitigate ISI by reducing LED transmission signaling density. This paper proposes a robust decoding framework that maintains full LED signaling density. We introduce a pilot-aided geometric recognition method that uses a PSF-constrained Hough transform and circle-center alignment refinement. \textbf{In addition, radial distortion correction and vignetting-aware compensation are incorporated to restore geometric consistency and suppress edge-related detection errors.} By leveraging prior structural knowledge from pilot frames, the system effectively separates overlapping LED signals under severe optical distortion. Experimental results on a real-world VLC testbed confirm that the proposed method achieves superior decoding accuracy and throughput compared to conventional Hough-based and low-density baseline methods. The results highlight its potential for high-efficiency VLC applications in interference-prone environments.

Masataka Kobayashi, Shintaro Shiba, Quan Kong et al.

With the growing adoption of autonomous driving, the advancement of sensor technology is crucial for ensuring safety and reliable operation. Sensor fusion techniques that combine multiple sensors such as LiDAR, radar, and cameras have proven effective, but the integration of multiple devices increases both hardware complexity and cost. Therefore, developing a single sensor capable of performing multiple roles is highly desirable for cost-efficient and scalable autonomous driving systems. Event cameras have emerged as a promising solution due to their unique characteristics, including high dynamic range, low latency, and high temporal resolution. These features enable them to perform well in challenging lighting conditions, such as low-light or backlit environments. Moreover, their ability to detect fine-grained motion events makes them suitable for applications like pedestrian detection and vehicle-to-infrastructure communication via visible light. In this study, we present a method for distance estimation using a monocular event camera and a roadside LED bar. By applying a phase-only correlation technique to the event data, we achieve sub-pixel precision in detecting the spatial shift between two light sources. This enables accurate triangulation-based distance estimation without requiring stereo vision. Field experiments conducted in outdoor driving scenarios demonstrated that the proposed approach achieves over 90% success rate with less than 0.5-meter error for distances ranging from 20 to 60 meters. Future work includes extending this method to full position estimation by leveraging infrastructure such as smart poles equipped with LEDs, enabling event-camera-based vehicles to determine their own position in real time. This advancement could significantly enhance navigation accuracy, route optimization, and integration into intelligent transportation systems.