68 research outputs found
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions
The Internet has made several giant leaps over the years, from a fixed to a
mobile Internet, then to the Internet of Things, and now to a Tactile Internet.
The Tactile Internet goes far beyond data, audio and video delivery over fixed
and mobile networks, and even beyond allowing communication and collaboration
among things. It is expected to enable haptic communication and allow skill set
delivery over networks. Some examples of potential applications are
tele-surgery, vehicle fleets, augmented reality and industrial process
automation. Several papers already cover many of the Tactile Internet-related
concepts and technologies, such as haptic codecs, applications, and supporting
technologies. However, none of them offers a comprehensive survey of the
Tactile Internet, including its architectures and algorithms. Furthermore, none
of them provides a systematic and critical review of the existing solutions. To
address these lacunae, we provide a comprehensive survey of the architectures
and algorithms proposed to date for the Tactile Internet. In addition, we
critically review them using a well-defined set of requirements and discuss
some of the lessons learned as well as the most promising research directions
Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing
Wireless communication at the terahertz (THz) frequency bands (0.1-10THz) is
viewed as one of the cornerstones of tomorrow's 6G wireless systems. Owing to
the large amount of available bandwidth, THz frequencies can potentially
provide wireless capacity performance gains and enable high-resolution sensing.
However, operating a wireless system at the THz-band is limited by a highly
uncertain channel. Effectively, these channel limitations lead to unreliable
intermittent links as a result of a short communication range, and a high
susceptibility to blockage and molecular absorption. Consequently, such
impediments could disrupt the THz band's promise of high-rate communications
and high-resolution sensing capabilities. In this context, this paper
panoramically examines the steps needed to efficiently deploy and operate
next-generation THz wireless systems that will synergistically support a
fellowship of communication and sensing services. For this purpose, we first
set the stage by describing the fundamentals of the THz frequency band. Based
on these fundamentals, we characterize seven unique defining features of THz
wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless
architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and
communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques,
and 7) Real-time network optimization. These seven defining features allow us
to shed light on how to re-engineer wireless systems as we know them today so
as to make them ready to support THz bands. Furthermore, these features
highlight how THz systems turn every communication challenge into a sensing
opportunity. Ultimately, the goal of this article is to chart a forward-looking
roadmap that exposes the necessary solutions and milestones for enabling THz
frequencies to realize their potential as a game changer for next-generation
wireless systems.Comment: 26 pages, 6 figure
The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review
Network latency will be a critical performance metric for the Fifth Generation (5G) networks
expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input
multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion,
especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will
face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network
set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability
and flexibility compared to prior existing deployed technologies. The scalability dimension caters
for meeting rapid demand as new applications evolve. While flexibility complements the scalability
dimension by investigating novel non-stacked protocol architecture. The goal of this review paper
is to deploy ultra-low latency reduction framework for 5G communications considering flexibility
and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing
is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new
technologies of software defined network (SDN), network function virtualization (NFV) and fog
networking. This review paper will contribute significantly towards the future implementation of
flexible and high capacity ultra-low latency 5G communications
Towards Tactile Internet in Beyond 5G Era: Recent Advances, Current Issues and Future Directions
Tactile Internet (TI) is envisioned to create a paradigm shift from the content-oriented
communications to steer/control-based communications by enabling real-time transmission of haptic information (i.e., touch, actuation, motion, vibration, surface texture) over Internet in addition to the conventional audiovisual and data traffics. This emerging TI technology, also considered as the next evolution phase of Internet of Things (IoT), is expected to create numerous opportunities for technology markets in a wide variety of applications ranging from teleoperation systems and Augmented/Virtual Reality (AR/VR) to automotive safety and eHealthcare towards addressing the complex problems of human society. However, the realization of TI over wireless media in the upcoming Fifth Generation (5G) and beyond networks creates various non-conventional communication challenges and stringent requirements
in terms of ultra-low latency, ultra-high reliability, high data-rate connectivity, resource allocation, multiple access and quality-latency-rate tradeoff. To this end, this paper aims to provide a holistic view on wireless TI along with a thorough review of the existing state-of-the-art, to identify and analyze the involved technical issues, to highlight potential solutions and to propose future research directions. First, starting with the vision of TI and recent advances and a review of related survey/overview articles, we present a generalized framework for wireless TI in the Beyond 5G Era including a TI architecture, the main technical requirements, the key application areas and potential enabling technologies. Subsequently, we provide a comprehensive review of the existing TI works by broadly categorizing them into three main paradigms; namely, haptic communications, wireless AR/VR, and autonomous, intelligent and cooperative mobility systems. Next, potential enabling technologies across physical/Medium Access Control (MAC) and network layers are identified and discussed in detail. Also, security and privacy issues of TI applications are discussed
along with some promising enablers. Finally, we present some open research challenges and recommend promising future research directions
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Self-Evolving Integrated Vertical Heterogeneous Networks
6G and beyond networks tend towards fully intelligent and adaptive design in
order to provide better operational agility in maintaining universal wireless
access and supporting a wide range of services and use cases while dealing with
network complexity efficiently. Such enhanced network agility will require
developing a self-evolving capability in designing both the network
architecture and resource management to intelligently utilize resources, reduce
operational costs, and achieve the coveted quality of service (QoS). To enable
this capability, the necessity of considering an integrated vertical
heterogeneous network (VHetNet) architecture appears to be inevitable due to
its high inherent agility. Moreover, employing an intelligent framework is
another crucial requirement for self-evolving networks to deal with real-time
network optimization problems. Hence, in this work, to provide a better insight
on network architecture design in support of self-evolving networks, we
highlight the merits of integrated VHetNet architecture while proposing an
intelligent framework for self-evolving integrated vertical heterogeneous
networks (SEI-VHetNets). The impact of the challenges associated with
SEI-VHetNet architecture, on network management is also studied considering a
generalized network model. Furthermore, the current literature on network
management of integrated VHetNets along with the recent advancements in
artificial intelligence (AI)/machine learning (ML) solutions are discussed.
Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are
identified. Finally, the potential future research directions for advancing the
autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table
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