Symbol Rate Maximization in Rolling-Shutter OCC: Design and Implementation Considerations

TL;DR

The paper tackles maximizing symbol rate in rolling-shutter OCC by modeling the camera processing as a rectangular matched-filter with exposure time $T_{ m exp}$ and row-rate sampling $f_{ m row}=1/T_{ m exp}$. It analyzes how imperfect time synchronization introduces inter-symbol interference (ISI) and derives a three-tap ISI model, then develops a practical solution using frame-based LS channel estimation and a zero-forcing equalizer to recover transmitted $M$-PAM symbols at the upper-bound rate. Experimental validation with a rolling-shutter camera and a PD shows that the proposed model closely matches reality and that linear equalization effectively mitigates ISI, enabling operation at rates approaching the camera’s Nyquist limit. The work demonstrates that high-rate OCC is achievable with off-the-shelf hardware by applying established digital-communication techniques to the camera-based receiver, bridging theory and practice for VLC-to-camera links.

Abstract

Optical Camera Communication (OCC) systems can take advantage of the row-by-row scanning process of rolling-shutter cameras to capture the fast variations of light intensity coming from Visible Light Communication (VLC) LED-based transmitters. In order to study the maximum data rate that is feasible in such kind of OCC systems, this paper presents its equivalent digital communication system model in which the rolling-shutter camera is modeled as a rectangular matched-filter whose time width is equal to the exposure time of the camera, followed by a sampling process at the pixel row sweep rate of the camera. Based on the proposed rolling-shutter camera model, the maximum symbol rate that such OCC systems can support is experimentally demonstrated, and the impact of imperfect time synchronization between the VLC transmitter and the rolling-shutter OCC receiver is characterized in the form of Inter-Symbol Interference (ISI). The equivalent three-tap channel model that results from this process is experimentally validated and the generated ISI is compensated with the use of linear equalization in reception. Simulation and experimental results show a strong correlation between them, demonstrating that the proposed approach can be used to make the OCC system work at the Nyquist sampling rate, which is equivalent to the pixel row sweep rate of the rolling-shutter camera used in reception.

Figures (8)

• Figure 1: System model of the proposed OCC system. The VLC rectangular pulses have a duration $T_{\rm s}$, whereas the camera exposure time is equal to $T_{\rm exp}$.
• Figure 2: Illustration of the rolling shutter camera sensor procedures with perfect time synchronization between VLC transmitter and OCC receiver. The intensity modulated symbols with duration $T_{\rm s}$ are integrated during a time period equal to the exposure time $T_{\rm exp}$. The discrete time signal sequence that is found at the bottom is equivalent to the stripe pattern that is observed on the camera image that is found on the right-hand side part of the figure.
• Figure 3: Illustration of the output signal obtained by the equivalent OCC system model in case of perfect synchronization between transmitter and receiver. Image stripes at the bottom do not show ISI as expected in this situation.
• Figure 4: Illustration of the output signal obtained by the equivalent OCC system model in case of a time offset $\delta(t)$ between transmitter and receiver. Image stripes at the bottom do show ISI that depends on the time offset.
• Figure 5: Experimental demonstration of received signal by the rolling-shutter camera in case of different time offsets measured as percentage of symbol time.