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 ◽  
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 ◽  
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 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’.

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.

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

2019 ◽  
Author(s):  
Phuc Duc Nguyen
Keyword(s):  
Visible Light ◽  
High Speed ◽  
Large Scale ◽  
Response Times ◽  
Vlsi Architecture ◽  
Visible Light Communication ◽  
Visible Light Communications ◽  
Soft Decision ◽  
Soft Decoding ◽  
Positioning Systems

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.

scholarly journals High-speed visible light communication systems based on Si-substrate LEDs with multiple superlattice interlayers

PhotoniX ◽  
2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Fangchen Hu ◽  
Shouqing Chen ◽  
Yuyi Zhang ◽  
Guoqiang Li ◽  
Peng Zou ◽  
...  
Keyword(s):  
Visible Light ◽  
Radio Frequency ◽  
Communication Systems ◽  
High Speed ◽  
Visible Light Communication ◽  
Data Rate ◽  
Si Substrate ◽  
Theoretical Derivation ◽  
Wall Plug Efficiency ◽  
The Impact

AbstractHigh-speed visible light communication (VLC), as a cutting-edge supplementary solution in 6G to traditional radio-frequency communication, is expected to address the tension between continuously increased demand of capacity and currently limited supply of radio-frequency spectrum resource. The main driver behind the high-speed VLC is the presence of light emitting diode (LED) which not only offers energy-efficient lighting, but also provides a cost-efficient alternative to the VLC transmitter with superior modulation potential. Particularly, the InGaN/GaN LED grown on Si substrate is a promising VLC transmitter to simultaneously realize effective communication and illumination by virtue of beyond 10-Gbps communication capacity and Watt-level output optical power. In previous parameter optimization of Si-substrate LED, the superlattice interlayer (SL), especially its period number, is reported to be the key factor to improve the lighting performance by enhancing the wall-plug efficiency, but few efforts were made to investigate the influence of SLs on VLC performance. Therefore, to optimize the VLC performance of Si-substrate LEDs, we for the first time investigated the impact of the SL period number on VLC system through experiments and theoretical derivation. The results show that more SL period number is related to higher signal-to-noise ratio (SNR) via improving the wall-plug efficiency. In addition, by using Levin-Campello bit and power loading technology, we achieved a record-breaking data rate of 3.37 Gbps over 1.2-m free-space VLC link under given optimal SL period number, which, to the best of our knowledge, is the highest data rate for a Si-substrate LED-based VLC system.

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