7 research outputs found
Deep Learning for Optimal Deployment of UAVs with Visible Light Communications
In this paper, the problem of dynamical deployment of unmanned aerial
vehicles (UAVs) equipped with visible light communication (VLC) capabilities
for optimizing the energy efficiency of UAV-enabled networks is studied. In the
studied model, the UAVs can simultaneously provide communications and
illumination to service ground users. Since ambient illumination increases the
interference over VLC links while reducing the illumination threshold of the
UAVs, it is necessary to consider the illumination distribution of the target
area for UAV deployment optimization. This problem is formulated as an
optimization problem which jointly optimizes UAV deployment, user association,
and power efficiency while meeting the illumination and communication
requirements of users. To solve this problem, an algorithm that combines the
machine learning framework of gated recurrent units (GRUs) with convolutional
neural networks (CNNs) is proposed. Using GRUs and CNNs, the UAVs can model the
long-term historical illumination distribution and predict the future
illumination distribution. Given the prediction of illumination distribution,
the original nonconvex optimization problem can be divided into two
sub-problems and is then solved using a low-complexity, iterative algorithm.
Then, the proposed algorithm enables UAVs to determine the their deployment and
user association to minimize the total transmit power. Simulation results using
real data from the Earth observations group (EOG) at NOAA/NCEI show that the
proposed approach can achieve up to 68.9% reduction in total transmit power
compared to a conventional optimal UAV deployment that does not consider the
illumination distribution and user association.Comment: This paper has been accepted by IEEE Transactions on Wireless
Communications. arXiv admin note: text overlap with arXiv:1909.0755
A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks
The fifth generation (5G) mobile networks are envisaged to enable a plethora
of breakthrough advancements in wireless technologies, providing support of a
diverse set of services over a single platform. While the deployment of 5G
systems is scaling up globally, it is time to look ahead for beyond 5G systems.
This is driven by the emerging societal trends, calling for fully automated
systems and intelligent services supported by extended reality and haptics
communications. To accommodate the stringent requirements of their prospective
applications, which are data-driven and defined by extremely low-latency,
ultra-reliable, fast and seamless wireless connectivity, research initiatives
are currently focusing on a progressive roadmap towards the sixth generation
(6G) networks. In this article, we shed light on some of the major enabling
technologies for 6G, which are expected to revolutionize the fundamental
architectures of cellular networks and provide multiple homogeneous artificial
intelligence-empowered services, including distributed communications, control,
computing, sensing, and energy, from its core to its end nodes. Particularly,
this paper aims to answer several 6G framework related questions: What are the
driving forces for the development of 6G? How will the enabling technologies of
6G differ from those in 5G? What kind of applications and interactions will
they support which would not be supported by 5G? We address these questions by
presenting a profound study of the 6G vision and outlining five of its
disruptive technologies, i.e., terahertz communications, programmable
metasurfaces, drone-based communications, backscatter communications and
tactile internet, as well as their potential applications. Then, by leveraging
the state-of-the-art literature surveyed for each technology, we discuss their
requirements, key challenges, and open research problems
A prospective look: key enabling technologies, applications and open research topics in 6G networks
The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is mainly driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks, which are expected to bring transformative changes to this premise. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. In particular, the present paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a comprehensive study of the 6G vision and outlining seven of its disruptive technologies, i.e., mmWave communications, terahertz communications, optical wireless communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss the associated requirements, key challenges, and open research problems. These discussions are thereafter used to open up the horizon for future research directions