scholarly journals Carrierless amplitude and phase modulation in wireless visible light communication systems

2020 ◽  
Vol 378 (2169) ◽  
pp. 20190181 ◽  
Author(s):  
N. Bamiedakis ◽  
R. V. Penty ◽  
I. H. White
Keyword(s):  
Visible Light ◽  
Communication Systems ◽  
High Speed ◽  
Low Cost ◽  
Visible Light Communication ◽  
Practical Implementation ◽  
Visible Light Communications ◽  
Modulation Formats ◽  
Spectrally Efficient ◽  
Basic Features

Visible light communications (VLCs) have attracted considerable interest in recent years owing to the potential to simultaneously achieve data transmission and illumination using low-cost light-emitting diodes (LEDs). However, the high-speed capability of such links is typically limited by the low bandwidth of LEDs. As a result, spectrally efficient advanced modulation formats have been considered for use in VLC links in order to mitigate this issue and enable higher data rates. Carrierless amplitude and phase (CAP) modulation is one such spectrally efficient scheme that has attracted significant interest in recent years owing to its good potential and practical implementation. In this paper, we introduce the basic features of CAP modulation and review its use in the context of indoor VLC systems. We describe some of its attributes and inherent limitations, present related advances aiming to improve its performance and potential and report on recent experimental demonstrations of LED-based VLC links employing CAP modulation. This article is part of the theme issue ‘Optical wireless communication’.

scholarly journals Towards Federated Learning-Enabled Visible Light Communication in 6G Systems

2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Ernesto Damiani ◽  
...  
Keyword(s):  
Visible Light ◽  
Communication Systems ◽  
High Speed ◽  
Large Scale ◽  
Low Cost ◽  
Visible Light Communication ◽  
Future Research ◽  
Communication Overhead ◽  
Green Communications ◽  
Raw Data

<div>Visible light communication is envisaged as a promising enabling technology for sixth generation (6G) and beyond networks. It was introduced as a key enabler for reliable massive-scale connectivity, mainly thanks to its simple and low-cost implementation which require minor variations to the existing indoor lighting systems. The key features of VLC allow offloading data traffic from the current congested radio frequency (RF) spectrum in order to achieve effective short-range, high speed, and green communications. However, several challenges prevent the realization of the full potentials of VLC, namely the limited modulation bandwidth of light emitting diodes, the interference resulted from ambient light, the effects of optical diffuse reflection, the non-linearity of devices, and the random receiver orientation. Meanwhile, centralized machine learning (ML) techniques have exhibited great potentials in handling different challenges in communication systems. Specifically, it has been recently shown that ML algorithms exhibit superior capabilities in handling complicated network tasks, such as channel equalization, estimation and modeling, resources allocation, opportunistic spectrum access control, non-linearity compensation, performance monitoring, detection, decoding/encoding, and network optimization. Nevertheless, concerns relating to privacy and communication overhead when sharing raw data of the involved clients with a server constitute major bottlenecks in large-scale implementation of centralized ML techniques. This has motivated the emergence of a new distributed ML paradigm, namely federated learning (FL). This method can reduce the cost associated with transferring the raw data, and preserve clients privacy by training ML model locally and collaboratively at the clients side. Thus, the integration of FL in VLC networks can provide ubiquitous and reliable implementation of VLC systems. Based on this, for the first time in the open literature, we provide an overview about VLC technology and FL. Then, we introduce FL and its integration in VLC networks and provide an overview on the main design aspects. Finally, we highlight some interesting future research directions of FL that are envisioned to boost the performance of VLC systems. </div>

scholarly journals Towards Federated Learning-Enabled Visible Light Communication in 6G Systems

2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Paschalis C. Sofotasios
Keyword(s):  
Visible Light ◽  
Communication Systems ◽  
High Speed ◽  
Large Scale ◽  
Low Cost ◽  
Visible Light Communication ◽  
Future Research ◽  
Communication Overhead ◽  
Green Communications ◽  
Raw Data

<div>Visible light communication is envisaged as a promising enabling technology for sixth generation (6G) and beyond networks. It was introduced as a key enabler for reliable massive-scale connectivity, mainly thanks to its simple and low-cost implementation which require minor variations to the existing indoor lighting systems. The key features of VLC allow offloading data traffic from the current congested radio frequency (RF) spectrum in order to achieve effective short-range, high speed, and green communications. However, several challenges prevent the realization of the full potentials of VLC, namely the limited modulation bandwidth of light emitting diodes, the interference resulted from ambient light, the effects of optical diffuse reflection, the non-linearity of devices, and the random receiver orientation. Meanwhile, centralized machine learning (ML) techniques have exhibited great potentials in handling different challenges in communication systems. Specifically, it has been recently shown that ML algorithms exhibit superior capabilities in handling complicated network tasks, such as channel equalization, estimation and modeling, resources allocation, opportunistic spectrum access control, non-linearity compensation, performance monitoring, detection, decoding/encoding, and network optimization. Nevertheless, concerns relating to privacy and communication overhead when sharing raw data of the involved clients with a server constitute major bottlenecks in large-scale implementation of centralized ML techniques. This has motivated the emergence of a new distributed ML paradigm, namely federated learning (FL). This method can reduce the cost associated with transferring the raw data, and preserve clients privacy by training ML model locally and collaboratively at the clients side. Thus, the integration of FL in VLC networks can provide ubiquitous and reliable implementation of VLC systems. Based on this, for the first time in the open literature, we provide an overview about VLC technology and FL. Then, we introduce FL and its integration in VLC networks and provide an overview on the main design aspects. Finally, we highlight some interesting future research directions of FL that are envisioned to boost the performance of VLC systems. </div>

scholarly journals Towards Federated Learning-Enabled Visible Light Communication in 6G Systems

2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Ernesto Damiani ◽  
...  
Keyword(s):  
Visible Light ◽  
Communication Systems ◽  
High Speed ◽  
Large Scale ◽  
Low Cost ◽  
Visible Light Communication ◽  
Future Research ◽  
Communication Overhead ◽  
Green Communications ◽  
Raw Data

<div>Visible light communication is envisaged as a promising enabling technology for sixth generation (6G) and beyond networks. It was introduced as a key enabler for reliable massive-scale connectivity, mainly thanks to its simple and low-cost implementation which require minor variations to the existing indoor lighting systems. The key features of VLC allow offloading data traffic from the current congested radio frequency (RF) spectrum in order to achieve effective short-range, high speed, and green communications. However, several challenges prevent the realization of the full potentials of VLC, namely the limited modulation bandwidth of light emitting diodes, the interference resulted from ambient light, the effects of optical diffuse reflection, the non-linearity of devices, and the random receiver orientation. Meanwhile, centralized machine learning (ML) techniques have exhibited great potentials in handling different challenges in communication systems. Specifically, it has been recently shown that ML algorithms exhibit superior capabilities in handling complicated network tasks, such as channel equalization, estimation and modeling, resources allocation, opportunistic spectrum access control, non-linearity compensation, performance monitoring, detection, decoding/encoding, and network optimization. Nevertheless, concerns relating to privacy and communication overhead when sharing raw data of the involved clients with a server constitute major bottlenecks in large-scale implementation of centralized ML techniques. This has motivated the emergence of a new distributed ML paradigm, namely federated learning (FL). This method can reduce the cost associated with transferring the raw data, and preserve clients privacy by training ML model locally and collaboratively at the clients side. Thus, the integration of FL in VLC networks can provide ubiquitous and reliable implementation of VLC systems. Based on this, for the first time in the open literature, we provide an overview about VLC technology and FL. Then, we introduce FL and its integration in VLC networks and provide an overview on the main design aspects. Finally, we highlight some interesting future research directions of FL that are envisioned to boost the performance of VLC systems. </div>

scholarly journals Towards Federated Learning-Enabled Visible Light Communication in 6G Systems

2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Paschalis C. Sofotasios
Keyword(s):  
Visible Light ◽  
Communication Systems ◽  
High Speed ◽  
Large Scale ◽  
Low Cost ◽  
Visible Light Communication ◽  
Future Research ◽  
Communication Overhead ◽  
Green Communications ◽  
Raw Data

<div>Visible light communication is envisaged as a promising enabling technology for sixth generation (6G) and beyond networks. It was introduced as a key enabler for reliable massive-scale connectivity, mainly thanks to its simple and low-cost implementation which require minor variations to the existing indoor lighting systems. The key features of VLC allow offloading data traffic from the current congested radio frequency (RF) spectrum in order to achieve effective short-range, high speed, and green communications. However, several challenges prevent the realization of the full potentials of VLC, namely the limited modulation bandwidth of light emitting diodes, the interference resulted from ambient light, the effects of optical diffuse reflection, the non-linearity of devices, and the random receiver orientation. Meanwhile, centralized machine learning (ML) techniques have exhibited great potentials in handling different challenges in communication systems. Specifically, it has been recently shown that ML algorithms exhibit superior capabilities in handling complicated network tasks, such as channel equalization, estimation and modeling, resources allocation, opportunistic spectrum access control, non-linearity compensation, performance monitoring, detection, decoding/encoding, and network optimization. Nevertheless, concerns relating to privacy and communication overhead when sharing raw data of the involved clients with a server constitute major bottlenecks in large-scale implementation of centralized ML techniques. This has motivated the emergence of a new distributed ML paradigm, namely federated learning (FL). This method can reduce the cost associated with transferring the raw data, and preserve clients privacy by training ML model locally and collaboratively at the clients side. Thus, the integration of FL in VLC networks can provide ubiquitous and reliable implementation of VLC systems. Based on this, for the first time in the open literature, we provide an overview about VLC technology and FL. Then, we introduce FL and its integration in VLC networks and provide an overview on the main design aspects. Finally, we highlight some interesting future research directions of FL that are envisioned to boost the performance of VLC systems. </div>

scholarly journals Finger-Gesture Recognition for Visible Light Communication Systems Using Machine Learning

2021 ◽  
Vol 11 (24) ◽  
pp. 11582
Author(s):  
Julian Webber ◽  
Abolfazl Mehbodniya ◽  
Rui Teng ◽  
Ahmed Arafa ◽  
Ahmed Alwakeel
Keyword(s):  
Visible Light ◽  
Gesture Recognition ◽  
Video Processing ◽  
Communication Systems ◽  
High Speed ◽  
Short Term Memory ◽  
Light Transmission ◽  
Light Emitting Diode ◽  
Visible Light Communication ◽  
Visible Light Communications

Gesture recognition (GR) has many applications for human-computer interaction (HCI) in the healthcare, home, and business arenas. However, the common techniques to realize gesture recognition using video processing are computationally intensive and expensive. In this work, we propose to task existing visible light communications (VLC) systems with gesture recognition. Different finger movements are identified by training on the light transitions between fingers using the long short-term memory (LSTM) neural network. This paper describes the design and implementation of the gesture recognition technique for a practical VLC system operating over a distance of 48 cm. The platform uses a single low-cost light-emitting diode (LED) and photo-diode sensor at the receiver side. The system recognizes gestures from interruptions in the direct light transmission, and is therefore suitable for high-speed communication. Gesture recognition accuracies were conducted for five gestures, and results demonstrate that the proposed system is able to accurately identify the gestures in up to 88% of cases.

scholarly journals Polymer colour converter with very high modulation bandwidth for visible light communications

2017 ◽  
Vol 5 (35) ◽  
pp. 8916-8920 ◽  
Author(s):  
D. A. Vithanage ◽  
A. L. Kanibolotsky ◽  
S. Rajbhandari ◽  
P. P. Manousiadis ◽  
M. T. Sajjad ◽  
...  
Keyword(s):  
Visible Light ◽  
High Speed ◽  
Visible Light Communication ◽  
Modulation Bandwidth ◽  
Visible Light Communications ◽  
Semiconducting Polymer ◽  
High Modulation ◽  
Very High

We report the synthesis, photophysics and application of a novel semiconducting polymer as a colour converter for high speed visible light communication.

scholarly journals Experimental Demonstration of Special-Shaped 32-Quadrature Amplitude Modulation Constellations for Visible Light Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Xinyue Guo ◽  
Shuangshuang Li ◽  
Yang Guo
Keyword(s):  
Visible Light ◽  
Amplitude Modulation ◽  
High Speed ◽  
Light Emitting Diode ◽  
Rapid Development ◽  
Average Power ◽  
Visible Light Communication ◽  
Quadrature Amplitude Modulation ◽  
Visible Light Communications ◽  
Transmission Distance

With the rapid development of light-emitting diode, visible light communication (VLC) has become a candidate technology for the next generation of high-speed indoor wireless communication. In this paper, we investigate the performance of the 32-quadrature amplitude modulation (32-QAM) constellation shaping schemes for the first time, where two special circular constellations, named Circular (4, 11, 17) and Circular (1, 5, 11, 15), and a triangular constellation are proposed based on the Shannon’s criterion. Theoretical analysis indicates that the triangular constellation scheme has the largest minimum Euclidian distance while the Circular (4, 11, 17) scheme achieves the lowest peak-to-average power ratio (PAPR). Experimental results show that the bit error rate performance is finally decided by the value of PAPR in the VLC system due to the serious nonlinearity of the LED, where the Circular (4, 11, 17) scheme always performs best under the 7% preforward error correction threshold of 3.8 × 10−3 with 62.5Mb/s transmission data rate and 1-meter transmission distance.

An Integrated High-Speed Full Duplex Coherent OFDM-PON and Visible-Light Communication System

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Simarpreet Kaur ◽  
Mahendra Kumar ◽  
Ashu Verma
Keyword(s):  
Visible Light ◽  
Optical Networks ◽  
High Speed ◽  
Light Emitting Diode ◽  
Low Cost ◽  
Dispersion Compensation ◽  
Optical Network ◽  
Visible Light Communication ◽  
Passive Optical Network ◽  
Full Duplex

AbstractWe demonstrated a full duplex hybrid passive optical network and indoor optical wireless system employing coherent optical frequency division multiplexing. To accomplish reliable transmission in passive optical networks integrated visible-light communication (VLC), yellow light-emitting diode and infrared LED is used in downstream and upstream, respectively, for intra building network. In order to support high data rate, pulse-width reduction scheme based on dispersion compensation fiber is incorporated and system successfully covered the distance of 50 km. A data stream at the rate of 30 Gb/s is transmitted for each user out of eight users. VLC-supported users are catered with the bit rate of 1.87 Gb/s over 150 cm and in order to realize a low-cost system, visible and infrared LEDs are used in downlink and uplink, respectively.

Researching the Information of Transmission Technology Based on Traffic Lights

2014 ◽  
Vol 644-650 ◽  
pp. 4538-4541
Author(s):  
Qiang Li ◽  
Xin Rui Zhang
Keyword(s):  
Visible Light ◽  
Image Recognition ◽  
Communication Technology ◽  
High Speed ◽  
Visible Light Communication ◽  
Qr Code ◽  
Visible Light Communications ◽  
Traffic Light ◽  
Traffic Lights ◽  
Very High

This design is based on Visible Light Communication Technology, to achieve outdoor visible light communications and image recognition etc. through traffic lights. It will play a role on promoting the utilization of traffic lights. The system uses a LED dot matrix to imitate the traffic light, loading QR Code information on the LED dot matrix and then transporting it in a very high-speed flashing. In receiving terminal, first, webcam OV7670 collects information which from the LED dot matrix, then conveys the picture to FPGA, which is the processor. FPGA will handle the picture by gray scale processing, medium filtering and binary processing at last. Thus, the picture from the LED dot matrix will change to ‘0’ and ‘1’ in binary area. Secondly, as there’s a relationship between LED dot matrix and webcam pixels, we can count how many pixels represent one LED. Finally, we can decode the QR Code based on its own style, and display the final result on the TFT screen.

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