Wireless optical OFDM implementation for aircraft cabin communication links

Marinos, D.; Aidinis, C. J.; Schmitt, Nikolaus P.; Klaue, Jirka; Schalk, Josef; Pistner, T.; Kouros, Pavlos

doi:10.1109/iswpc.2010.5483801

Cited by 3 publications

(1 citation statement)

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“…Considering the sufficiently high rate of modulation, flickering is undetectable by the human eyes [2]. The potential of VLC is being explored for a number of applications including highspeed (i.e., beyond the trade-mark level of Gbps) data communications in indoor environments, vehicular networks [3], airplane cabins [4], trains [5] and intelligent traffic lights management [6], [7], indoor positioning [8], motion detection [9], occupancy detection [10], ranging and detection [11] among others. However, to fully and effectively be able to adopt and implement the VLC technology in real environments there are still a number of challenges, which need to be addressed, including the physical layer (higher data rates versus the transmission span), interference management [12], medium access control (MAC) [13], integration with existing optical fiber and radio frequency wireless systems, mobility [14], shadowing [15] or peak-to-average-power ratio [16].…”

Section: Li-tect: 3d Monitoring and Shape Detection Using Visible Ligmentioning

confidence: 99%

Li-Tect: 3-D Monitoring and Shape Detection Using Visible Light Sensors

et al. 2019

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In this paper, we propose Li-Tect, an algorithm to detect the shape of an object located in an indoor environment using low cost optical elements through sensing the environment's light. The algorithm analyzes, relying on the predictability of optical propagation paths, how much light is expected to propagate in the absence of obstructions caused by the presence of an object. Then, based on the received light when the object is in the room, the algorithm infers the shape of the object. In addition, the algorithm considers the reflected paths from surfaces in order to determine the object's estimated shape. We study five different scenarios characterized by different levels of complexity, room sizes and a range of reflection nodes. The algorithm is also tested in a real prototype where several experiments are carried out in two scenarios to demonstrate the capabilities of Li-Tect in two and three dimensional monitoring and shape detection cases. Finally, the results show that the shape and the detection of objects in the scenarios can be easily acquired with high accuracy, even if the number of transceivers is reduced.

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