An in-Depth Survey of Visible Light Communication Based Positioning Systems <s> Image Sensors <s> In this paper, a novel scheme for data reception in a mobile phone using visible light communications (VLC) is proposed. The camera of the smartphone is used as a receiver in order to capture the continuous changes in state (on-off) of the light, which are invisible to the human eye. The information is captured in the camera in the form of light and dark bands which are then decoded by the smartphone and the received message is displayed. By exploiting the rolling shutter effect of CMOS sensors, a data rate much higher than the camera frame rate is achieved. <s> BIB001 </s> An in-Depth Survey of Visible Light Communication Based Positioning Systems <s> Image Sensors <s> Indoor localization is the fundamental capability for indoor service robots and indoor applications on mobile devices. To realize that, the cost of sensors is of great concern. In order to decode the signal carried out by the LED beacons, we propose two reliable solutions using common sensors available on consumer electronic devices. Firstly, we introduce a dedicated analog sensor, which can be directly connected to the microphone input of a computer or a smart phone. It decodes both the signal pattern and signal strength of a beacon. Secondly, we utilize rolling-shutter cameras to decode the signal pattern, providing potential solutions to the localization of hand-held devices with cameras. In contrast to existing widely-applied indoor localization approaches, like vision-based and laser-based methods, our approach reveals its advantages as low-cost, globally consistent and it retains the potential applications using Visible Light Communication(VLC). We also study the characteristics of the proposed solutions under typical indoor conditions by experiments. <s> BIB002 </s> An in-Depth Survey of Visible Light Communication Based Positioning Systems <s> Image Sensors <s> The omnipresence of indoor lighting makes it an ideal vehicle for pervasive communication with mobile devices. In this paper, we present a communication scheme that enables interior ambient LED lighting systems to send data to mobile devices using either cameras or light sensors. By exploiting rolling shutter camera sensors that are common on tablets, laptops and smartphones, it is possible to detect high-frequency changes in light intensity reflected off of surfaces and in direct line-of-sight of the camera. We present a demodulation approach that allows smartphones to accurately detect frequencies as high as 8kHz with 0.2kHz channel separation. In order to avoid humanly perceivable flicker in the lighting, our system operates at frequencies above 2kHz and compensates for the non-ideal frequency response of standard LED drivers by adjusting the light's duty-cycle. By modulating the PWM signal commonly used to drive LED lighting systems, we are able to encode data that can be used as localization landmarks. We show through experiments how a binary frequency shift keying modulation scheme can be used to transmit data at 1.25 bytes per second (fast enough to send an ID code) from up to 29 unique light sources simultaneously in a single collision domain. We also show how tags can demodulate the same signals using a light sensor instead of a camera for low-power applications. <s> BIB003 </s> An in-Depth Survey of Visible Light Communication Based Positioning Systems <s> Image Sensors <s> This paper elucidates the fundamentals of visible light communication systems that use the rolling shutter mechanism of CMOS sensors. All related information involving different subjects, such as photometry, camera operation, photography and image processing, are studied in tandem to explain the system. Then, the system performance is analyzed with respect to signal quality and data rate. To this end, a measure of signal quality, the signal to interference plus noise ratio (SINR), is formulated. Finally, a simulation is conducted to verify the analysis. <s> BIB004
Compare to PDs, image sensor can provide much more useful information related to the position of LEDs, to enable vision analysis algorithms. With the ability to separate light sources, image sensors inherently do not require any multiplexing mechanisms. Also, image sensors can stand against ambient light much better than a PD. However, image sensors have a big limitation related to data rate. To obtain the information, a sequence of grabbed images is processed to find the presence and absence of LEDs, which represent the logical 1 and 0, respectively. Generally, the achieved data rate is less than or equal to the camera frame rate. Currently, the frame rate of a smart phone camera is 60 fps, which indicates a data rate limited to 30 bps when a single LED is used. Obviously, such a low data rate is insufficient for transmitting even the simplest positioning information. To achieve a higher data rate, a simple but expensive solution is to use a high speed camera to capture hundreds to thousands of image of LEDs per second. For communication purpose, the data rate should be as high as possible. To further increase the data rate, LED arrays can be used instead of LEDs to transmit light patterns which convey much more data in a single frame. For positioning purpose, the data rate doesn't need to be very high and thus another solution, that is utilizing the rolling shutter effect of CMOS image sensors, can be used. The technique of VLC using rolling shutter was proposed in BIB001 and analyzed in BIB004 . This technique is inexpensive in that it just requires a normal CMOS sensor camera which is equipped in most cameras and smart phones. However, to achieve a decent data rate, that is tens of kpbs, the distance from camera to LED must be very close. For example, the communication distance in BIB001 BIB004 is less than 15 cm. Obviously, this distance is impractical for any positioning system. Fortunately, the required distance can be lengthened up to a few meters by using large LED panels or illuminated surfaces. The fingerprinting positioning system in BIB002 used white walls as the illuminated surfaces to achieve the working distance of a few meters. However, using large LED panels or illuminated surfaces cannot solve all the problems. For an absolute positioning algorithm using single view geometry, multiple LEDs must be in the view of the camera and thus the size of each LED in the image is small. Consequently, the achieved data rate can be very low. In BIB003 , the camera on a smart phone used the rolling shutter effect to receive the signal transmitted from multiple LEDs. Experiments showed that a data rate of 1.25 bytes per second, which is just fast enough to send an ID code, was achieved. In some applications where the size of LEDs need to be small or the camera moves fast, this technique might not give a sufficient data rate for positioning.