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Open accessJournal ArticleDOI: 10.3390/S21051709

6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap

02 Mar 2021-Sensors (Multidisciplinary Digital Publishing Institute)-Vol. 21, Iss: 5, pp 1709
Abstract: The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to have a proper insight into the vision and requirements of 6G. Second, we provide a panoramic view of the enabling technologies proposed to facilitate 6G and introduce emerging 6G applications such as multi-sensory–extended reality, digital replica, and more. Next, the technology-driven challenges, social, psychological, health and commercialization issues posed to actualizing 6G, and the probable solutions to tackle these challenges are discussed extensively. Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism. Furthermore, we discuss the multi-faceted communication capabilities of 6G that will contribute significantly to global sustainability and how 6G will bring about a dramatic change in the business arena. Finally, we highlight the research trends, open research issues, and key take-away lessons for future research exploration in 6G wireless communication.

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Topics: Wireless network (57%)
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16 results found


Open accessJournal ArticleDOI: 10.1016/J.VEHCOM.2021.100398
Abstract: Employing machine learning into 6G vehicular networks to support vehicular application services is being widely studied and a hot topic for the latest research works in the literature. This article provides a comprehensive review of research works that integrated reinforcement and deep reinforcement learning algorithms for vehicular networks management with an emphasis on vehicular telecommunications issues. Vehicular networks have become an important research area due to their specific features and applications such as standardization, efficient traffic management, road safety, and infotainment. In such networks, network entities need to make decisions to maximize network performance under uncertainty. To achieve this goal, Reinforcement Learning (RL) can effectively solve decision-making problems. However, the state and action spaces are massive and complex in large-scale wireless networks. Hence, RL may not be able to find the best strategy in a reasonable time. Therefore, Deep Reinforcement Learning (DRL) has been developed to combine RL with Deep Learning (DL) to overcome this issue. In this survey, we first present vehicular networks and give a brief overview of RL and DRL concepts. Then we review RL and especially DRL approaches to address emerging issues in 6G vehicular networks. We finally discuss and highlight some unresolved challenges for further study.

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3 Citations


Open accessJournal ArticleDOI: 10.3390/APP11178117
31 Aug 2021-Applied Sciences
Abstract: Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard.

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Topics: Wireless network (53%), 5G (50%)

2 Citations


Proceedings ArticleDOI: 10.1109/IWCMC51323.2021.9498628
Abhishek Gupta1, Xavier Fernando1, Olivia Das1Institutions (1)
28 Jun 2021-
Abstract: This paper investigates the reliability assessment and availability prediction techniques used in modeling of advanced (next generation) wireless communication networks. The 5G, 5G+, beyond 5G (B5G) and 6G communication technologies are leading to emerging applications of wireless communication that use cloud computing, edge computing, and fog computing. In the last decade, various user-centric and service-oriented networks such as internet of things (IoT), smart cities, smart homes, smart grids, drones, and unmanned aerial vehicles (UAV) have been deployed that use technologies such as network function virtualization (NVF), software defined networking (SDN), and 5G. This has led to proliferation of IoT devices and IoT applications in various critical usage systems such as intelligent transportation systems, smart healthcare, and e-commerce. The availability and reliability of wireless connectivity in IoT devices and nodes is of significant importance as unavailability of nodes or end-user devices even for a millisecond could cause failure of healthcare systems or lead to malfunction of connected and autonomous vehicles, or compromise the smart grids power generation and distribution, leading to fatal outcomes.

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Topics: Edge computing (59%), Smart grid (55%), Cloud computing (54%) ... show more

1 Citations


Open accessJournal ArticleDOI: 10.3390/S21093197
04 May 2021-Sensors
Abstract: Fifth-generation (5G) networks will not satisfy the requirements of the latency, bandwidth, and traffic density in 2030 and beyond, and next-generation wireless communication networks with revolutionary enabling technologies will be required. Beyond 5G (B5G)/sixth-generation (6G) networks will achieve superior performance by providing advanced functions such as ultralow latency, ultrahigh reliability, global coverage, massive connectivity, and better intelligence and security levels. Important aspects of B5G/6G networks require the modification and exploitation of promising physical-layer technologies. This Special Issue (SI) presents research efforts to identify and discuss the novel techniques, technical challenges, and promising solution methods of physical-layer technologies with a vision of potential involvement in the B5G/6G era. In particular, this SI presents innovations and concepts, including nonorthogonal multiple access, massive multiple-input multiple-output (MIMO), energy harvesting, hybrid satellite terrestrial relays, Internet of Things-based home automation, millimeter-wave bands, device-to-device communication, and artificial-intelligence or machine-learning techniques. Further, this SI covers the proposed solutions, including MIMO antenna design, modulation detection, interference management, hybrid precoding, and statistical beamforming along with their performance improvements in terms of performance metrics, including bit error rate, outage probability, ergodic sum rate, spectrum efficiency, and energy efficiency.

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Topics: Spectral efficiency (54%), 5G (54%), MIMO (53%) ... show more

1 Citations


Open accessJournal ArticleDOI: 10.1364/OE.434880
Seonghyeon Cho1, Hyunchae Chun1Institutions (1)
30 Aug 2021-Optics Express
Abstract: Fluorescent planar concentrators have been proposed as optical concentrators that can have both a wide field of view and a high optical gain stemming from a large collection area for optical wireless communications. However, the fluorescent concentrators with such a large collection area often lead to a low light coupling efficiency due to the edge coupling mechanism leading to a considerable optical power loss. In this work, an analysis of the light coupling efficiency enhancement in the electrical power gain is presented. In particular, a practical method to improve the coupling efficiency by introducing edge and back reflection using Lambertian-, specular-, and retro-reflectors is presented. It is demonstrated that by choosing the optimal reflectors, the received signal strength can be improved by more than a factor of two. Also demonstrated with the proposed method is a data rate more than 1.12 Gbps with bit error rate less than 3.8 × 10−3 using a DC-biased optical orthogonal frequency division multiplexing. This is, to the best of our knowledge, the first Gbps class demonstration using a commercial fluorescent planar concentrator.

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277 results found


Open accessJournal ArticleDOI: 10.1109/JSAC.2014.2328098
Jeffrey G. Andrews1, Stefano Buzzi2, Wan Choi, Stephen V. Hanly3  +3 moreInstitutions (6)
Abstract: What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

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Topics: Backward compatibility (51%)

6,462 Citations


Open accessJournal ArticleDOI: 10.1186/S40537-016-0043-6
Abstract: Machine learning and data mining techniques have been used in numerous real-world applications. An assumption of traditional machine learning methodologies is the training data and testing data are taken from the same domain, such that the input feature space and data distribution characteristics are the same. However, in some real-world machine learning scenarios, this assumption does not hold. There are cases where training data is expensive or difficult to collect. Therefore, there is a need to create high-performance learners trained with more easily obtained data from different domains. This methodology is referred to as transfer learning. This survey paper formally defines transfer learning, presents information on current solutions, and reviews applications applied to transfer learning. Lastly, there is information listed on software downloads for various transfer learning solutions and a discussion of possible future research work. The transfer learning solutions surveyed are independent of data size and can be applied to big data environments.

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1,650 Citations


Open accessJournal ArticleDOI: 10.1109/TCCN.2017.2758370
Timothy J. O'Shea1, Jakob Hoydis2Institutions (2)
Abstract: We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end reconstruction task that seeks to jointly optimize transmitter and receiver components in a single process. We show how this idea can be extended to networks of multiple transmitters and receivers and present the concept of radio transformer networks as a means to incorporate expert domain knowledge in the machine learning model. Lastly, we demonstrate the application of convolutional neural networks on raw IQ samples for modulation classification which achieves competitive accuracy with respect to traditional schemes relying on expert features. This paper is concluded with a discussion of open challenges and areas for future investigation.

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Topics: Deep learning (59%), Autoencoder (57%), Artificial neural network (55%) ... show more

1,384 Citations


Open accessJournal ArticleDOI: 10.1109/TWC.2019.2936025
Qingqing Wu1, Rui Zhang1Institutions (1)
Abstract: Intelligent reflecting surface (IRS) is a revolutionary and transformative technology for achieving spectrum and energy efficient wireless communication cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each being able to reflect the incident signal independently with an adjustable phase shift so as to collaboratively achieve three-dimensional (3D) passive beamforming without the need of any transmit radio-frequency (RF) chains. In this paper, we study an IRS-aided single-cell wireless system where one IRS is deployed to assist in the communications between a multi-antenna access point (AP) and multiple single-antenna users. We formulate and solve new problems to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users’ individual signal-to-interference-plus-noise ratio (SINR) constraints. Moreover, we analyze the asymptotic performance of IRS’s passive beamforming with infinitely large number of reflecting elements and compare it to that of the traditional active beamforming/relaying. Simulation results demonstrate that an IRS-aided MIMO system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains. We also draw useful insights into optimally deploying IRS in future wireless systems.

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Topics: Beamforming (58%), MIMO (56%), Wireless network (54%) ... show more

1,344 Citations


Open accessJournal ArticleDOI: 10.1109/COMST.2015.2495297
Lav Gupta1, Raj Jain1, Gabor Vaszkun2Institutions (2)
Abstract: Unmanned aerial vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications, where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions more efficiently and economically as compared to single UAV systems. However, there are many issues to be resolved before effective use of UAVs can be made to provide stable and reliable context-specific networks. Much of the work carried out in the areas of mobile ad hoc networks (MANETs), and vehicular ad hoc networks (VANETs) does not address the unique characteristics of the UAV networks. UAV networks may vary from slow dynamic to dynamic and have intermittent links and fluid topology. While it is believed that ad hoc mesh network would be most suitable for UAV networks yet the architecture of multi-UAV networks has been an understudied area. Software defined networking (SDN) could facilitate flexible deployment and management of new services and help reduce cost, increase security and availability in networks. Routing demands of UAV networks go beyond the needs of MANETS and VANETS. Protocols are required that would adapt to high mobility, dynamic topology, intermittent links, power constraints, and changing link quality. UAVs may fail and the network may get partitioned making delay and disruption tolerance an important design consideration. Limited life of the node and dynamicity of the network lead to the requirement of seamless handovers, where researchers are looking at the work done in the areas of MANETs and VANETs, but the jury is still out. As energy supply on UAVs is limited, protocols in various layers should contribute toward greening of the network. This paper surveys the work done toward all of these outstanding issues, relating to this new class of networks, so as to spur further research in these areas.

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1,152 Citations


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