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![Qualcomm's 5G Vision [52].](profile/Sadiq-Idris-2/publication/340121319/figure/fig2/AS:968070055075843@1607817295915/Qualcomms-5G-Vision-52.jpg)
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![Fig. 3. Qualcomm's 5G Vision [52].](profile/Sadiq-Idris-2/publication/340121319/figure/fig2/AS:968070055075843@1607817295915/Qualcomms-5G-Vision-52_Q320.jpg)
![Differences of VLC and LiFi Technologies [3]](profile/Sadiq-Idris-2/publication/340121319/figure/tbl1/AS:968070059282432@1607817296008/Differences-of-VLC-and-LiFi-Technologies-3_Q320.jpg)
The fifth-generation (5G) mobile network is the next paradigm shift in the revolutionary era of the wireless communication technologies that will break the backward compatibility of today’s communication systems. Visible Light Communication (VLC) and Light Fidelity (LiFi) technologies are among the potential candidates that are expected to be utili...
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... 5G is envisioned to enhance a common core network (user-centric) that will simultaneously support 4G and WiFi access connectivity with multimode devices enabling seamless services and edgeless connectivity. To explain how VLC and LiFi technologies can be integrated into 5G technology, we adopt the Qualcomm's 5G proposed vision shown in Figure 3. ...
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In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobi...
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... As a subfield of AI, FL will have a role to play in promoting VLC applications. The features that characterise VLC systems, including high spatial reuse, ultra-low-latency, ultra-high-data rates, and inherent security, provide the ingredients needed for the efficient implementation of FL algorithms [91]. The main purpose of FL is to secure data privacy and reduce communication overhead. ...
New technological advancements in wireless networks have enlarged the number of connected devices. The unprecedented surge of data volume in wireless systems empowered by artificial intelligence (AI) opens up new horizons for providing ubiquitous data-driven intelligent services. Traditional cloud-centric machine learning (ML)-based services are implemented by centrally collecting datasets and training models. However, this conventional training technique encompasses two challenges: (i) high communication and energy cost and (ii) threatened data privacy. In this article, we introduce a comprehensive survey of the fundamentals and enabling technologies of federated learning (FL), a newly emerging technique coined to bring ML to the edge of wireless networks. Moreover, an extensive study is presented detailing various applications of FL in wireless networks and highlighting their challenges and limitations. The efficacy of FL is further explored with emerging prospective beyond fifth-generation (B5G) and sixth-generation (6G) communication systems. This survey aims to provide an overview of the state-of-the-art FL applications in key wireless technologies that will serve as a foundation to establish a firm understanding of the topic. Lastly, we offer a road forward for future research directions.
... OWC systems operate in the IR, VL and UV frequency bands and are generally considered to be more mature than THz systems, with deployments in various applications [123]. OWC technologies include, Visible Light Communication (VLC), Light Fidelity (LiFi), Optical Camera Communication (OCC), Free-Space Optics (FSO), and Light Detection and Ranging (LiDAR) [27], [126], [127]. Moreover, OWC can be considered as a complementary technology to existing RF-based wireless communication technologies [123]. ...
... However, it is worth noting that the standardization efforts of OWC systems, including VLC, is not limited to IEEE. Other large-scale organizations, such as the Visible Light Communication Consortium (VLCC) in Japan and the European OMEGA project, have also played a significant role in the standardization and development of VLC technology [126]. In 2003, Japan began the standardization of VLC systems, and interest in the technology has been increasing since then [135]. ...
The upcoming sixth generation (6G) mobile communication system is expected to operate across a wide range of spectrum that includes not only the bands used by previous generations but also higher frequency bands such as millimeter wave (mmWave), which are currently assigned to fifth generation (5G) networks, terahertz (THz), and optical spectrum. By utilizing a broader range of frequencies, it will be possible to support 6G applications with faster data rates, higher capacity, and lower latency. However, the higher frequency bands pose unique challenges such as higher path loss, absorption loss, and engineering difficulties for antennas and radio frequency (RF) circuitry design, which require advanced technologies and innovative solutions. Given that the spectrum is a scarce resource, efficient management is crucial to ensure the most effective exploitation of frequency bands. The spectrum management has evolved over the years, with different approaches being used to assign and utilize frequency bands. In this paper, we provide a review of spectrum management approaches, including their use in awarding 5G spectrum, and explore their expected use in 6G. We then offer a brief overview of spectrum sharing and its role in enabling the efficient use of spectrum resources. The regulations, standardization, features, limitations, and potential use cases of higher frequency bands such as, mmWave, THz, and visible light (VL) are analyzed to provide a comprehensive understanding of the spectrum options available for the upcoming 6G technology.
... Instead of the conventional MIMO systems that use two or four antennas, massive MIMO systems use big array antenna components that provide significant capacity benefits. For indoor coverage, multiple technologies such as millimeter-wave communication [24], small cells, Wi-Fi, ultrawideband [25], and visible light communication [26] are suitable for short-range, high data rate responses. However, visible light and millimeter-wave responses require the utilization of higher frequencies, which are not typically used in cellular responses. ...
Fifth-generation (5G) cellular networks are state-of-the-art wireless technologies revolutionizing all wireless systems. The fundamental goals of 5G are to increase network capacity, improve data rates, and reduce end-to-end latency. Therefore, 5G can support many devices connected to the Internet and realize the Internet of Things (IoT) vision. Though 5 G provides significant features for mobile wireless networks, some challenges still need to be addressed. Although 5 G offers valuable capabilities for mobile wireless networks, specific issues still need to be resolved. This article thoroughly introduces 5G technology, detailing its needs, infrastructure, features, and difficulties. In addition, it summarizes all the requirements and specifications of the 5G network based on the 3rd Generation Partnership Project (3GPP) Releases 15–17. Finally, this study discusses the key specifications challenges of 5G wireless networks.
... Driven by the ever-increasing penetration of the digitization era in the globe, wireless data traffic with high network capacity demand is expected to substantially increase [1]. Ongoing research on future wireless networks that could plausibly satisfy future client data needs has consistently intensified [2], [3], [4]. Along with the fifth-generation (5G) technologies, visible light communication (VLC) has attracted considerable attention for high-speed and short-range wireless communications due to its many inherent advantages such as license-free spectrum, low-cost front-ends, high security, and strong immunity to electromagnetic interference [3], [4]. ...
... Ongoing research on future wireless networks that could plausibly satisfy future client data needs has consistently intensified [2], [3], [4]. Along with the fifth-generation (5G) technologies, visible light communication (VLC) has attracted considerable attention for high-speed and short-range wireless communications due to its many inherent advantages such as license-free spectrum, low-cost front-ends, high security, and strong immunity to electromagnetic interference [3], [4]. To be considered as a high-capacity wireless broadband technology, the developed VLC systems can effectively support low-latency communications that are pivotal to ensure realtime functionality in interactive communications of machines in industrial automation applications [5] and support multiple users with simultaneous network access [6]. ...
In this paper, we propose a theoretical framework for analyzing the performance of the short-packet communication (SPC) in a downlink non-orthogonal multiple access (NOMA) visible light communication (VLC) system in which one light emitting diode (LED) communicates with two single-photodiode users. The analytical expression of the block error rate (BLER) is approximated by Gaussian-Chebyshev quadrature method, based on which the reliability, throughput, and latency expressions are deduced. Further, we jointly optimize power allocation coefficients and transmission rates to maximize sum throughput of the SPC-NOMA VLC system. The numerical results show that (i) our proposed system well satisfies the stringent requirements of the ultra-reliable and low latency communication (URLLC) at signal-to-noise ratio (SNR) larger than 130 dB; (ii) SPC-NOMA VLC systems outperform SPC- orthogonal multiple access (OMA) VLC systems in terms of reliability, latency, and throughput; (iii) the impacts of block-length, power allocation coefficients, transmission rates, and LED semi-angle are examined.
... FL as a subfield of AI will have a role to play in promoting VLC applications. The features that characterise VLC systems, including high spatial reuse, ultra-low-latency, ultra-high-data rates, and inherent security, provide the ingredients needed for the efficient implementation of FL algorithms [147]. The main purpose of FL is to secure data privacy and reduce communication overhead. ...
The unprecedented surge of data volume in wireless networks empowered with artificial intelligence (AI) opens up new horizons for providing ubiquitous data-driven intelligent services. Traditional cloud-centric machine learning (ML)-based services are implemented by collecting datasets and training models centrally. However, this conventional training technique encompasses two challenges: (i) high communication and energy cost due to increased data communication, (ii) threatened data privacy by allowing untrusted parties to utilise this information. Recently, in light of these limitations, a new emerging technique, coined as federated learning (FL), arose to bring ML to the edge of wireless networks. FL can extract the benefits of data silos by training a global model in a distributed manner, orchestrated by the FL server. FL exploits both decentralised datasets and computing resources of participating clients to develop a generalised ML model without compromising data privacy. In this article, we introduce a comprehensive survey of the fundamentals and enabling technologies of FL. Moreover, an extensive study is presented detailing various applications of FL in wireless networks and highlighting their challenges and limitations. The efficacy of FL is further explored with emerging prospective beyond fifth generation (B5G) and sixth generation (6G) communication systems. The purpose of this survey is to provide an overview of the state-of-the-art of FL applications in key wireless technologies that will serve as a foundation to establish a firm understanding of the topic. Lastly, we offer a road forward for future research directions.
... As tecnologias por luz visível estão sendo estudas por pesquisadores para conciliaçãoàs redes de quinta geração (5G) [117], principalmente pelas vantagens que oferecem. Essas vantagens estão no baixo custo, segurança, alta precisão, alta taxas de comunicação, etc., que também são características buscadas pelas redes 5G [118]. ...
... Em [117] e [118], são apresentados cenários nos quais as técnicas por luz visível são implementadas como uma subcamada de comunicação nas bordas da rede, voltadas para aplicações em ambientes internos. Já em [119],é apresentada a aplicação dessas técnicas, em conjunto com o 5G, com o foco para cenários externos de curto alcance, mais especificamente para uma rede de veículos inteligentes (V2V), dado a enorme massa de dados gerada por esses veículos. ...
The autonomous mobility field is changing worldwide, mainly due to new technologies developed by different actors. However, there are still open challenges related to vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I), as well as vehicle localization, a crucial topic in navigation. In this scope, this document reports the study of visible light positioning and communication techniques (VLP and VLC, respectively) to trace the state of the art of these technologies. It seeks their applicability in the field of intelligent mobility to integrate Advanced Driver Assistance Systems (ADAS) with them. Moreover, we present the current challenges of these technologies in the intelligent vehicles field, mainly in the urban environment. The literature cataloged results justify the application proposal and provide an important resource for those interested in this subject.
... Recently, the optical wireless transmission has a huge contribution to emerge a new generation of communication networks with the flexibility and high reliability (Idris 2019;Aziz 2020;Al-Khaffaf and Hujijo 2018). This technology relies upon the optical radiation to convey the data through the free space. ...
This paper reports a novel architecture of hybrid multi-mode fiber (MMF) and visible light communication (VLC) system. The cloud VLC Access Point introduces for the first time. The central station transmits 10 Gbits of baseband optical signal generated by using the LED source over 4 km of MMF to the cloud VLC (C-VLC) terminal point at the smart home network. We assume that all optical background noises have been considered in the VLC channel. A 10 Gbits transferred over 25 m free space optical (FSO) channel using white LED source. A forward error correction channel encoding has been used with non- return to zero to transmit the data. All optical background noises have been added to the FSO channel such as white light, red, green, flashlight, yellow, ultraviolet, blue and spectrum light sources. The VLC receiving system has an optical filter and maximum likelihood sequence estimation equalizer. The harmonic components are discard using the low pass filter. The simulation results show that the system model has a typical performance with zero bit error rate.
... As tecnologias por luz visível estão sendo estudas por pesquisadores para conciliaçãoàs redes de quinta geração (5G) [117], principalmente pelas vantagens que oferecem. Essas vantagens estão no baixo custo, segurança, alta precisão, alta taxas de comunicação, etc., que também são características buscadas pelas redes 5G [118]. ...
... Em [117] e [118], são apresentados cenários nos quais as técnicas por luz visível são implementadas como uma subcamada de comunicação nas bordas da rede, voltadas para aplicações em ambientes internos. Já em [119],é apresentada a aplicação dessas técnicas, em conjunto com o 5G, com o foco para cenários externos de curto alcance, mais especificamente para uma rede de veículos inteligentes (V2V), dado a enorme massa de dados gerada por esses veículos. ...
The autonomous mobility field is changing worldwide, mainly due to new technologies developed by different actors. However, there are still open challenges related to vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I), as well as vehicle localization, a crucial topic in navigation. In this scope, this document reports the study of visible light positioning and communication techniques (VLP and VLC, respectively) to trace the state of the art of these technologies. It seeks their applicability in the field of intelligent mobility to integrate Advanced Driver Assistance Systems (ADAS) with them. Moreover, we present the current challenges of these technologies in the intelligent vehicles field, mainly in the urban environment. The literature cataloged results justify the application proposal and provide an important resource for those interested in this subject.
... The end-devices need to not only opportunistically switch between access devices from the same access technology, e.g., between WiFi Access Points (APs), but also between access devices from multiple RATs. This challenge is further complicated by including new RATs in B5G networks such as Light Fidelity (LiFi) or Visible Light Communication (VLC) [11]. The terms LiFi and VLC are used interchangeably. ...
The expected manifolds increase in the traffic and the massive number of connected Internet of Things (IoT) devices would be a challenge to ensure a certain Quality of Service (QoS) in Beyond 5G (B5G) networks. Due to the increased availability of processing and energy resources and heterogeneous QoS requirements in modern IoT nodes, a client-centric access device selection approach for QoS provisioning in multiple Radio Access Technologies (RATs) scenario is proposed in this paper. The proposed algorithm provides the ability to specify node-specific QoS requirements at each node, a better access device selection, and improved network scalability. For experimental evaluation, a hybrid indoor network consisting of Wireless Fidelity (WiFi) and Light Fidelity (LiFi) RATs has been considered. Experimental results show that the proposed technique outperforms several conventional client-based access device selection approaches by up to 32.66% in network emulation experiments and up to 50% in hardware experimentation. The contribution of this paper includes the proposed algorithm, its complexity and game-theory based convergence analyses, evaluation of the proposed algorithm using network emulation and hardware-based setups, and LiFi channel analysis. The analyses and results imply that the proposed algorithm could be utilized in next-generation IoT networks as it performs better than conventionally used access device selection techniques for QoS provisioning.
