June – August 2015 Intel Project Monthly Report
Next-Generation Cooperative Vehicle Safety System
Current team members:
Champion: Dr. Richard Roberts
PI and co-PI: Prof. Hsin-Mu (Michael) Tsai and Dr. Kate Ching-Ju Lin
Students: Hua-Yen Tseng (Master), Chung-Lin Chan (Master), Jing-Yeu Chen (Master), Ai-Ling
Chen (Master), You-Lin Wei (Master)
Graduated students: Chia-Fu Li (Master), Hsin-I Wu (Master, converted to full-time RA), KuanTing Chen (Master), Hui-Yu Lee (Master)
Communication with the champion:
Rick is on sabbatical until mid-September.
Rick, Kate, and Michael had a conference call in early July to go over the technical
materials that would be presented in the August F2F meeting. Rick pointed out a
few missing pieces of our ongoing research: (1) LiBeamScanner needs to be able to
handle situations that the receiver has arbitrary rotation with respect to the
transmitter. (2) Need to identify the applications which would be able to utilize the
multi-cam bandwidth expansion result.
Michael and Rick exchanged a few emails after the F2F. Michael reported that the
presentation and the demo went well at the F2F. The two also set up the plan to
prepare for the submission to IEEE 802.15.7r1’s call for proposal and the
presentation that will take place in November, next January, or next March’s IEEE
802 meeting.
1. LiBeamScanner
We developed LiBeamScanner, a novel indoor visible light positioning system that
utilizes only a single custom LED light bulb and a light sensor to achieve extremely high
positioning accuracy. At the physical layer, we propose a novel transmitter design that
allows information to be modulated onto very narrow light beams, projected to a large
number of fine-grained locations simultaneously. More importantly, these light beams
generate negligible interference to each other, as a result providing a high resolution for
enabling accurate positioning. Evaluation results of our prototype show that most of the
errors are less than 3cm and the average error does not exceed 5cm. The following two
figures show the distribution of positioning accuracy (left figure) at different spatial
locations (at 175cm distance) and the distribution of positioning accuracy at different
distances (right figure). The top, middle, and bottom lines of the boxes in the right figure
represent the 25%, 50%, and 75% percentiles.
Indoor Navigation System with Invisible Polarizer Marker and Visible Light Communications
In this system, we use commodity cameras as the receiver and modify off-the-shelf
LED light to become the transmitter, and thus it requires minimal additional cost. The main
idea is that when the camera captures images with the polarizer marker on the ceiling light
fixture, the orientation angle between the camera and polarizer marker can be estimated.
Utilizing VLC, at the time the LED also transmits its absolute location to the camera. The
device can then use these two pieces of information to estimate its own absolute location
when more than one LED light is captured in the image. Results show that the mean angle
error is always less than 10° for a distance up to 2.5 meters. The following two figures
show a typical usage scenario of our system (top figure) and the measured mean
positioning error at different rotation angles (bottom figure).
Bandwidth Expansion in Camera Communication Systems with Multi-camera Receiver
We proposed a novel technique to improve the throughput of CamCom system.
The system still utilizes a single LED as the transmitter but make use of multiple CMOS
cameras as the receiver. Our idea is to use multiple cameras to capture the signal of LED
with a frequency higher than the Nyquist frequency, effectively expanding the usable
bandwidth. Due to the different rolling shutter sampling rates of different cameras (the
inverse of the rolling shutter read-out time), the Nyquist frequency for different cameras
also differ. When the transmitted signal frequency exceeds the Nyquist frequency of a
particular camera, the signal will be observed as a lower frequency signal by the camera,
and the phenomenon is commonly known as aliasing. In this research, we propose a
scheme to correctly estimate the original transmitted frequency, which can be higher than
the Nyquist frequency of the cameras, by combining the results from multiple cameras.
Experimental results show that with this technique we can expand the usable bandwidth
by 5.7 times and the system throughput by approximately 30%.
Brief plan for next month:
1. Prepare a submission to IEEE Vehicular Networking Conference, summarizing the
measurement results and the findings (asymmetrical nature of the links) of the headlight
and taillight radiation pattern.
2. Resolve two important issues of LiBeamScanner (1) arbitrary rotation of the receiver (2) the
slow response time due to the length of the preamble signal.
3. Carry out VLC channel measurements in driving scenarios to further characterize the car-tocar VLC channel.

June – August 2015 Intel Project Monthly Report