## 3 OCC Performance Improvement
### Camera Sampling Rate and Shutter Speed  
The performance of OCC is greatly influenced by the sampling rate of the camera. High-frame-rate cameras contribute to high-data-rate communication. However, the majority of the currently available commercial cameras have low frame rates, which led researchers to introduce some undersampling techniques to communicate with these low-frame-rate cameras [8; 23]. Recalling Equation (6), it can be noted that the frame rate has a significant effect on the overall SINR and channel capacity.  
Figure 4: The strip configurations for OCC.  
Using high-frame-rate cameras leads to higher data rates. This is because using the on-off keying (OOK) scheme requires the sampling rate to be at least double the LED flickering frequency to satisfy the [PERSON] criterion [15]. For the undersampled frequency-shift OOK (UFSOOK), the modulation frequency is a multiple of the frame rate. Therefore, high data rates can be achieved for the same multiples using cameras with high frame rates.  
The shutter speed indicates the length of time for which a frame is exposed to light. The shutter speed plays an important role in OCC. A low shutter speed leads to blurring as the LED switches at a high speed. This increases the BER significantly. The shutter speed should be more than twice the frame rate for secure communication. Moreover, the shutter speed should be synchronized with the LED flickering rate as the synchronization establishes how many bits are transmitted during one exposure. As shown in Figure 5, the total number of detectable bits during one exposure is \(\mathrm{n_{b}}\). We assume that every pixel of the image sensor is exposed to light for the same amount of time. The opaque portions represent the closed periods of the camera shutter. For simplicity, we consider that the on and off periods of the camera shutter are the same and the total number of exposures per second is \(\mathrm{m}\). After synchronization, the number of detectable transmitted bits per exposure can be represented as  
\[\mathrm{n_{b}}=2\mathrm{ft_{e}},\ [\mathrm{t_{s}}\geq 2\mathrm{f_{r}}] \tag{13}\]  
where \(\mathrm{t_{e}}\) denotes the time of a single exposure for a particular frame, and \(\mathrm{t_{s}}\) indicates the shutter speed.  
The exposure time also affects the power received by the image sensor. Data decoding depends on the brightness level of the strips. The exposure time determines how much signal power will be allocated to each pixel. When the exposure time is increased, a higher intensity of light will illuminate the pixels, eventually increasing the signal strength. However, as the image is binarized, a short exposure time will increase the signal strength of the pixels containing the projected image of the LED as compared to the other pixels that result in LED detection with reduced complexity. In addition, longer exposure time will also increase the noise elements. On the contrary, there is a minimum received signal power below which the data cannot be decoded. The number of strips corresponding to that power is analyzed in the next section. Therefore, the exposure time should be set to a certain limit as if the signal strength of the pixels remains beyond the minimum extent.