scholarly journals Hardware Architectures of Visible Light Communication Transmitter and Receiver for Beacon-based Indoor Positioning Systems

Author(s):  
Phuc Duc Nguyen

High-speed applications of Visible Light Communications have been presented recently in which response times of photodiode-based VLC receivers are critical points. Typical VLC receiver routines, such as soft-decoding of run-length limited (RLL) codes and FEC codes was purely processed on embedded firmware, and potentially cause bottleneck at the receiver. To speed up the performance of receivers, ASIC-based VLC receiver could be the solution. Unfortunately, recent works on soft-decoding of RLL and FEC have shown that they are bulky and time-consuming computations. This causes hardware implementation of VLC receivers becomes heavy and unrealistic. In this paper, we introduce a compact Polar-code-based VLC receivers. in which flicker mitigation of the system can be guaranteed even without RLL codes. In particular, we utilized the centralized bit-probability distribution of a pre-scrambler and a Polar encoder to create a non-RLL flicker mitigation solution. At the receiver, a 3-bit soft-decision filter was implemented to analyze signals received from the VLC channel to extract log-likelihood ratio (LLR) values and feed them to the Polar decoder. Therefore, the proposed receiver could exploit the soft-decoding of the Polar decoder to improve the error-correction performance of the system. Due to the non-RLL characteristic, the receiver has a preeminent code-rate and a reduced complexity compared with RLL-based receivers. We present the proposed VLC receiver along with a novel very-large-scale integration (VLSI) architecture, and a synthesis of our design using FPGA/ASIC synthesis tools.

2017 ◽  
Vol 5 (35) ◽  
pp. 8916-8920 ◽  
Author(s):  
D. A. Vithanage ◽  
A. L. Kanibolotsky ◽  
S. Rajbhandari ◽  
P. P. Manousiadis ◽  
M. T. Sajjad ◽  
...  

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


2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Xinyue Guo ◽  
Shuangshuang Li ◽  
Yang Guo

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.


2014 ◽  
Vol 644-650 ◽  
pp. 4538-4541
Author(s):  
Qiang Li ◽  
Xin Rui Zhang

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.


2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Ernesto Damiani ◽  
...  

<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>


Author(s):  
N. Bamiedakis ◽  
R. V. Penty ◽  
I. H. White

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’.


2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Paschalis C. Sofotasios

<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>


2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Ernesto Damiani ◽  
...  

<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>


2021 ◽  
Author(s):  
Shimaa Naser ◽  
Lina Bariah ◽  
sami muhaidat ◽  
Mahmoud Al-Qutayri ◽  
Paschalis C. Sofotasios

<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>


2020 ◽  
Vol 12 (3) ◽  
pp. 69-73
Author(s):  
Guiling Sun ◽  
◽  
Weijian Zhao ◽  
Ruobin Wang ◽  
Xuanjie Li

Visible light communication (VLC) has attracted people's attention due to its wide range of spectrum resources and good privacy in recent year. But research on visible light communication is mostly focused on LED materials, transfer protocol, transmission rates, etc. Lack of research that connect the visible light communications with existing communications methods. In this paper, we propose an Ethernet-visible data conversion system based on FPGA, including Ethernet interface logic, bit-width conversion logic, data buffer logic, and visible light communication transceiver logic. The proposed system achieves Ethernet and visible light access, and realizes 1000Mbps Ethernet data and 625Mbps visible light data conversion. Through buffer control, Ethernet data can be completely and reliably transmitted from high speed to low speed. By defining the structure of visible light communication frame and adding data self-recovery mechanism, data transmission has higher stability on the path of visible light. The feasibility of the system is proved by actual measurements.


2021 ◽  
Vol 11 (24) ◽  
pp. 11582
Author(s):  
Julian Webber ◽  
Abolfazl Mehbodniya ◽  
Rui Teng ◽  
Ahmed Arafa ◽  
Ahmed Alwakeel

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.


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