10,005 research outputs found
Cooperative Hierarchical Caching in 5G Cloud Radio Access Networks (C-RANs)
Over the last few years, Cloud Radio Access Network (C-RAN) has arisen as a
transformative architecture for 5G cellular networks that brings the
flexibility and agility of cloud computing to wireless communications. At the
same time, content caching in wireless networks has become an essential
solution to lower the content-access latency and backhaul traffic loading,
which translate into user Quality of Experience (QoE) improvement and network
cost reduction. In this article, a novel Cooperative Hierarchical Caching (CHC)
framework in C-RAN is introduced where contents are jointly cached at the
BaseBand Unit (BBU) and at the Radio Remote Heads (RRHs). Unlike in traditional
approaches, the cache at the BBU, cloud cache, presents a new layer in the
cache hierarchy, bridging the latency/capacity gap between the traditional
edge-based and core-based caching schemes. Trace-driven simulations reveal that
CHC yields up to 80% improvement in cache hit ratio, 21% decrease in average
content-access latency, and 20% reduction in backhaul traffic load compared to
the edge-only caching scheme with the same total cache capacity. Before closing
the article, several challenges and promising opportunities for deploying
content caching in C-RAN are highlighted towards a content-centric mobile
wireless network.Comment: to appear on IEEE Network, July 201
Ultra Dense Networks: The New Wireless Frontier for Enabling 5G Access
The extreme traffic load that future wireless networks are expected to
accommodate requires a re-thinking of the system design. Initial estimations
indicate that, different from the evolutionary path of previous cellular
generations that was based on spectral efficiency improvements, the most
substantial amount of future system performance gains will be obtained by means
of network infrastructure densification. By increasing the density of
operator-deployed infrastructure elements, along with incorporation of
user-deployed access nodes and mobile user devices acting as "infrastructure
prosumers", it is expected that having one or more access nodes exclusively
dedicated to each user will become feasible, introducing the ultra dense
network (UDN) paradigm. Although it is clear that UDNs are able to take
advantage of the significant benefits provided by proximal transmissions and
increased spatial reuse of system resources, at the same time, large node
density and irregular deployment introduce new challenges, mainly due to the
interference environment characteristics that are vastly different from
previous cellular deployments. This article attempts to provide insights on
fundamental issues related to UDN deployment, such as determining the
infrastructure density required to support given traffic load requirements and
the benefits of network-wise coordination, demonstrating the potential of UDNs
for 5G wireless networks.Comment: to appear in IEEE Vehicular Technology Magazin
Autonomous Wireless Systems with Artificial Intelligence
This paper discusses technology and opportunities to embrace artificial
intelligence (AI) in the design of autonomous wireless systems. We aim to
provide readers with motivation and general AI methodology of autonomous agents
in the context of self-organization in real time by unifying knowledge
management with sensing, reasoning and active learning. We highlight
differences between training-based methods for matching problems and
training-free methods for environment-specific problems. Finally, we
conceptually introduce the functions of an autonomous agent with knowledge
management
A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
The ongoing deployment of 5G cellular systems is continuously exposing the
inherent limitations of this system, compared to its original premise as an
enabler for Internet of Everything applications. These 5G drawbacks are
currently spurring worldwide activities focused on defining the next-generation
6G wireless system that can truly integrate far-reaching applications ranging
from autonomous systems to extended reality and haptics. Despite recent 6G
initiatives1, the fundamental architectural and performance components of the
system remain largely undefined. In this paper, we present a holistic,
forward-looking vision that defines the tenets of a 6G system. We opine that 6G
will not be a mere exploration of more spectrum at high-frequency bands, but it
will rather be a convergence of upcoming technological trends driven by
exciting, underlying services. In this regard, we first identify the primary
drivers of 6G systems, in terms of applications and accompanying technological
trends. Then, we propose a new set of service classes and expose their target
6G performance requirements. We then identify the enabling technologies for the
introduced 6G services and outline a comprehensive research agenda that
leverages those technologies. We conclude by providing concrete recommendations
for the roadmap toward 6G. Ultimately, the intent of this article is to serve
as a basis for stimulating more out-of-the-box research around 6G.Comment: This paper has been accepted by IEEE Networ
Preserving Reliability to Heterogeneous Ultra-Dense Distributed Networks in Unlicensed Spectrum
This article investigates the prominent dilemma between capacity and
reliability in heterogeneous ultra-dense distributed networks, and advocates a
new measure of effective capacity to quantify the maximum sustainable data rate
of a link while preserving the quality-of-service (QoS) of the link in such
networks. Recent breakthroughs are brought forth in developing the theory of
the effective capacity in heterogeneous ultra-dense distributed networks.
Potential applications of the effective capacity are demonstrated on the
admission control, power control and resource allocation of such networks, with
substantial gains revealed over existing technologies. This new measure is of
particular interest to ultra-dense deployment of the emerging fifth-generation
(5G) wireless networks in the unlicensed spectrum, leveraging the capacity gain
brought by the use of the unlicensed band and the stringent reliability
sustained by 5G in future heterogeneous network environments
A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions
The fifth generation (5G) wireless network technology is to be standardized
by 2020, where main goals are to improve capacity, reliability, and energy
efficiency, while reducing latency and massively increasing connection density.
An integral part of 5G is the capability to transmit touch perception type
real-time communication empowered by applicable robotics and haptics equipment
at the network edge. In this regard, we need drastic changes in network
architecture including core and radio access network (RAN) for achieving
end-to-end latency on the order of 1 ms. In this paper, we present a detailed
survey on the emerging technologies to achieve low latency communications
considering three different solution domains: RAN, core network, and caching.
We also present a general overview of 5G cellular networks composed of software
defined network (SDN), network function virtualization (NFV), caching, and
mobile edge computing (MEC) capable of meeting latency and other 5G
requirements.Comment: Accepted in IEEE Communications Surveys and Tutorial
Artificial Intelligence-Defined 5G Radio Access Networks
Massive multiple-input multiple-output antenna systems, millimeter wave
communications, and ultra-dense networks have been widely perceived as the
three key enablers that facilitate the development and deployment of 5G
systems. This article discusses the intelligent agent in 5G base station which
combines sensing, learning, understanding and optimizing to facilitate these
enablers. We present a flexible, rapidly deployable, and cross-layer artificial
intelligence (AI)-based framework to enable the imminent and future demands on
5G and beyond infrastructure. We present example AI-enabled 5G use cases that
accommodate important 5G-specific capabilities and discuss the value of AI for
enabling beyond 5G network evolution
Big Data Analytics, Machine Learning and Artificial Intelligence in Next-Generation Wireless Networks
The next-generation wireless networks are evolving into very complex systems
because of the very diversified service requirements, heterogeneity in
applications, devices, and networks. The mobile network operators (MNOs) need
to make the best use of the available resources, for example, power, spectrum,
as well as infrastructures. Traditional networking approaches, i.e., reactive,
centrally-managed, one-size-fits-all approaches and conventional data analysis
tools that have limited capability (space and time) are not competent anymore
and cannot satisfy and serve that future complex networks in terms of operation
and optimization in a cost-effective way. A novel paradigm of proactive,
self-aware, self- adaptive and predictive networking is much needed. The MNOs
have access to large amounts of data, especially from the network and the
subscribers. Systematic exploitation of the big data greatly helps in making
the network smart, intelligent and facilitates cost-effective operation and
optimization. In view of this, we consider a data-driven next-generation
wireless network model, where the MNOs employ advanced data analytics for their
networks. We discuss the data sources and strong drivers for the adoption of
the data analytics and the role of machine learning, artificial intelligence in
making the network intelligent in terms of being self-aware, self-adaptive,
proactive and prescriptive. A set of network design and optimization schemes
are presented with respect to data analytics. The paper is concluded with a
discussion of challenges and benefits of adopting big data analytics and
artificial intelligence in the next-generation communication system
Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives
With advancements of next-generation programmable networks a traditional
rule-based decision-making may not be able to adapt effectively to changing
network and customer requirements and provide optimal customer experience.
Customer experience management (CEM) components and implementation challenges
with respect to operator, network, and business requirements must be understood
to meet required demands. This paper gives an overview of CEM components and
their design challenges. We elaborate on data analytics and artificial
intelligence driven CEM and their functional differences. This overview
provides a path toward autonomous CEM framework in next-generation networks and
sets the groundwork for future enhancements.Comment: 9 pages, 5 figure
Distinguished Capabilities of Artificial Intelligence Wireless Communication Systems
With the great success of artificial intelligence (AI) technologies in
pattern recognitions and signal processing, it is interesting to introduce AI
technologies into wireless communication systems. Currently, most of studies
are focused on applying AI technologies for solving old problems, e.g.,
wireless location accuracy and resource allocation optimization in wireless
communication systems. However, It is important to distinguish new capabilities
created by AI technologies and rethink wireless communication systems based on
AI running schemes. Compared with conventional capabilities of wireless
communication systems, three distinguished capabilities, i.e., the cognitive,
learning and proactive capabilities are proposed for future AI wireless
communication systems. Moreover, an intelligent vehicular communication system
is configured to validate the cognitive capability based on AI clustering
algorithm. Considering the revolutionary impact of AI technologies on the data,
transmission and protocol architecture of wireless communication systems, the
future challenges of AI wireless communication systems are analyzed. Driven by
new distinguished capabilities of AI wireless communication systems, the new
wireless communication theory and functions would indeed emerge in the next
round of the wireless communications revolution
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