# Color-Space-Based Visual-MIMO for V2X Communication +
## 2 Experimental Section
### Mobile Networking through Visual-MIMO  
In contrast to RF wireless channels, the visual-MIMO system will not be subject to multipath fading [9]. Since achievable bitrates of the visual-MIMO system are primarily dependent on receiver perspective, line-of-sight (LOS) availability, and the distance between the transmitter and receiver, our visual-MIMO protocols could benefit from networking information such as distance, angle, inter-symbol-interference (ISI), link bit rates, target color, and reference color (symbol). Such knowledge is useful both at the physical and network layers. If we send the reference color (symbol), we may achieve improvements in the SER performance using noise cancellation. By using the networking information of distance or SNR, we can determine the transition from the multiplexing mode to the diversity mode. The main challenge facing the deployment of vehicular _ad hoc_ networks (VANETs) is the lack of infrastructure. This makes cooperative diversity an ideal physical-layer solution for VANETs. A source node can get help from other nodes by relaying the information message to the destination node. This characteristic of the network allows multipath transmission strategies that are similar in concept to cooperative RF communications, but the former requires less coordination overhead. Consider a scenario shown in Figure 4[2; 9] involving three nodes, namely a source, a destination, and a potential relay. The relay is positioned between the two other nodes, but remains closer to the source than the destination (without obstructing the LOS between the source and destination). Because shorter distances allow higher multiplexing gain, it is likely that the link capacity between the source and the relay is greater than the other links. The highest throughput can be achieved by simultaneous transmission through the relay and on the direct link. The transmitters can again use networking information to determine the transmission strategies. We may also consider another V2X scenario of multiple access in which a destination node can receive the information from multiple source nodes simultaneously. For example, as shown in Figure 5, any driving car needs to communicate with forward vehicles, vehicles driving in the opposite direction and traffic infra-structures such as traffic lights. Figure 4: Multipath transmission strategies using geometric information. In this concept, which we call a visual-MIMO, optical transmissions by multiple transmitter elements are received by an array of photodiode elements (e.g., pixels in a CMOS camera). The image sensor in a camera is essentially an array of photodiodes and the camera lens provides a different narrow field of view for each photodiode. This creates a large number of highly directional receive elements (the camera pixels), which allows reduction of interference and noise and thereby can achieve large ranges, yet still maintain the wide field-of-view necessary for mobile communication [9]. Therefore, if the light sources of multiple nodes do not overlap within the field of view, it is possible to receive each light source by separating multiple sources through image processing techniques. Figure 6 shows an example of the divided region of interest (ROI) for communication. This divided communication area can be obtained by using various image processing techniques, such as the lane recognition, vehicle recognition, traffic sign recognition under driving traffic environment [10; 11]. By dividing the communication area in this way using image processing, we may achieve the simultaneous multiple access communication without inter-channel (inter-node) interferences. If we divide the node-specific communication area, we may communicate without interference. In this scenario example, we apply the GCM based visual-MIMO to the target color of a traffic light and we may guarantee the required SER performance under worse traffic conditions.