No abstract

Optical camera communications (OCC) research field has grown recently, aided by ubiquitous digital cameras; however, atmospheric conditions can restrict their feasibility in outdoor scenarios. In this work, we studied an experimental OCC system under environmental phenomena emulated in a laboratory chamber. We found that the heat-induced turbulence does not affect our system significantly, while the attenuation caused by fog does decrease the signal quality. For this reason, a novel strategy is proposed, using the camera’s built-in amplifier to overcome the optical power loss and to decrease the quantization noise induced by the analog-digital converter of the camera. The signal quality has been evaluated using the Pearson’s correlation coefficient with respect to a reference template signal, along with the signal-to-noise ratio that has been empirically evaluated. The amplification mechanism introduced allows our system to receive the OCC signal under heavy fog by gradually increasing the camera gain up to 16 dB, for meteorological visibility values down to 10 m, with a correlation coefficient of 0.9 with respect to clear conditions.

This paper investigates the performance of the neural network (NN) assisted motion detection (MD) over an indoor optical camera communication (OCC) link. The proposed study is based on the performance evaluation of various NN training algorithms, which provide efficient and reliable MD functionality along with vision, illumination, data communications and sensing in indoor OCC. To evaluate the proposed scheme, we have carried out an experimental investigation of a static indoor downlink OCC link employing a mobile phone front camera as the receiver and an 8 × 8 red, green and blue light-emitting diodes array as the transmitter. In addition to data transmission, MD is achieved using a camera to observe user's finger movement in the form of centroids via the OCC link. The captured motion is applied to the NN and is evaluated for a number of MD schemes. The results show that, resilient backpropagation based NN offers the fastest convergence with a minimum error of 10 −5 within the processing time window of 0.67 s and a success probability of 100 % for MD compared to other algorithms. We demonstrate that, the proposed system with motion offers a bit error rate which is below the forward error correction limit of 3.8 × 10 −3 , over a transmission distance of 1.17 m.

The fifth generation (5G) telecommunications standards are being developed to meet the growing demands for high-speed wireless networks (i.e., few tens of Gigabits per second). The 5G standard stems largely from an increasing number of users and plethora of different devices, collectively referred to as smart devices, connecting to a network as part of Internet-of-Things (IoT). A few potential technologies have emerged for 5G such as millimeter waves, massive multiple-input multiple-output, and small cell communications. Although these technologies would satisfy the requirements of 5G, there is a complementary alternative wireless technology of optical wireless communications (OWC), which is being considered. As part of OWC, visible light communications (VLC) and optical camera communications (OCC) are the most attractive options for 5G networks and beyond. VLC with huge frequency spectrum integrated with IoT can open up a wide range of indoor and outdoor applications as part of future smart environments. This paper provides an overview of the all-optical IoT (OIoT) focusing on VLC and OCC based potential applications and challenges as part of 5G standards. Keywords-Optical wireless communications (OWC); visible light communications (VLC); optical camera communications (OCC); Internet of things (IoT); light emitting diodes (LEDs). I.

In optical camera communications (OCC), the provision of both flicker-free illumination and high data rates are challenging issues, which can be addressed by utilizing the rolling-shutter (RS) property of the image sensors as the receiver (Rx). In this paper, we propose an RS-based multiple-input multiple-output OCC scheme for the Internet of things (IoT) application. A simplified design of multi-channel transmitter (Tx) using a 7.2 × 7.2 cm2 small 8 × 8 distributed light emitting diode (LED) array, based on grouping of LEDs, is proposed for flicker-free transmission. We carry out an experimental investigation of the indoor OCC system by employing a Raspberry Pi camera as the Rx, with RS capturing mode. Despite the small area of the display, flicker-free communication links within the range of 20–100 cm are established with data throughput of 960 to 120 bps sufficient for IoT. A method to extend link spans up to 1.8 m and the data throughput to 13.44 kbps using different configurations of multi-channel Tx is provided. The peak signal-to-noise ratio of ~14 and 16 dB and the rate of successfully received bits of 99.4 and 81% are measured for the shutter speeds of 200 and 800 µs for a link span of 1 m, respectively.

No abstract

No abstract

No abstract