1,017 research outputs found
Downlink Energy Efficiency of Power Allocation and Wireless Backhaul Bandwidth Allocation in Heterogeneous Small Cell Networks
The widespread application of wireless services and dense devices access have
triggered huge energy consumption. Because of the environmental and financial
considerations, energy-efficient design in wireless networks becomes an
inevitable trend. To the best of the authors' knowledge, energy-efficient
orthogonal frequency division multiple access heterogeneous small cell
optimization comprehensively considering energy efficiency maximization, power
allocation, wireless backhaul bandwidth allocation, and user Quality of Service
is a novel approach and research direction, and it has not been investigated.
In this paper, we study the energy-efficient power allocation and wireless
backhaul bandwidth allocation in orthogonal frequency division multiple access
heterogeneous small cell networks. Different from the existing resource
allocation schemes that maximize the throughput, the studied scheme maximizes
energy efficiency by allocating both transmit power of each small cell base
station to users and bandwidth for backhauling, according to the channel state
information and the circuit power consumption. The problem is first formulated
as a non-convex nonlinear programming problem and then it is decomposed into
two convex subproblems. A near optimal iterative resource allocation algorithm
is designed to solve the resource allocation problem. A suboptimal
low-complexity approach is also developed by exploring the inherent structure
and property of the energy-efficient design. Simulation results demonstrate the
effectiveness of the proposed algorithms by comparing with the existing
schemes.Comment: to appear in IEEE Transactions on Communication
A Survey on 5G: The Next Generation of Mobile Communication
The rapidly increasing number of mobile devices, voluminous data, and higher
data rate are pushing to rethink the current generation of the cellular mobile
communication. The next or fifth generation (5G) cellular networks are expected
to meet high-end requirements. The 5G networks are broadly characterized by
three unique features: ubiquitous connectivity, extremely low latency, and very
high-speed data transfer. The 5G networks would provide novel architectures and
technologies beyond state-of-the-art architectures and technologies. In this
paper, our intent is to find an answer to the question: "what will be done by
5G and how?" We investigate and discuss serious limitations of the fourth
generation (4G) cellular networks and corresponding new features of 5G
networks. We identify challenges in 5G networks, new technologies for 5G
networks, and present a comparative study of the proposed architectures that
can be categorized on the basis of energy-efficiency, network hierarchy, and
network types. Interestingly, the implementation issues, e.g., interference,
QoS, handoff, security-privacy, channel access, and load balancing, hugely
effect the realization of 5G networks. Furthermore, our illustrations highlight
the feasibility of these models through an evaluation of existing
real-experiments and testbeds.Comment: Accepted in Elsevier Physical Communication, 24 pages, 5 figures, 2
table
Heterogeneous Services Provisioning in Small Cell Networks with Cache and Mobile Edge Computing
In the area of full duplex (FD)-enabled small cell networks, limited works
have been done on consideration of cache and mobile edge communication (MEC).
In this paper, a virtual FD-enabled small cell network with cache and MEC is
investigated for two heterogeneous services, high-data-rate service and
computation-sensitive service. In our proposed scheme, content caching and FD
communication are closely combined to offer high-data-rate services without the
cost of backhaul resource. Computing offloading is conducted to guarantee the
delay requirement of users. Then we formulate a virtual resource allocation
problem, in which user association, power control, caching and computing
offloading policies and resource allocation are jointly considered. Since the
original problem is a mixed combinatorial problem, necessary variables
relaxation and reformulation are conducted to transfer the original problem to
a convex problem. Furthermore, alternating direction method of multipliers
(ADMM) algorithm is adopted to obtain the optimal solution. Finally, extensive
simulations are conducted with different system configurations to verify the
effectiveness of the proposed scheme
Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues
As a key technique for enabling artificial intelligence, machine learning
(ML) is capable of solving complex problems without explicit programming.
Motivated by its successful applications to many practical tasks like image
recognition, both industry and the research community have advocated the
applications of ML in wireless communication. This paper comprehensively
surveys the recent advances of the applications of ML in wireless
communication, which are classified as: resource management in the MAC layer,
networking and mobility management in the network layer, and localization in
the application layer. The applications in resource management further include
power control, spectrum management, backhaul management, cache management,
beamformer design and computation resource management, while ML based
networking focuses on the applications in clustering, base station switching
control, user association and routing. Moreover, literatures in each aspect is
organized according to the adopted ML techniques. In addition, several
conditions for applying ML to wireless communication are identified to help
readers decide whether to use ML and which kind of ML techniques to use, and
traditional approaches are also summarized together with their performance
comparison with ML based approaches, based on which the motivations of surveyed
literatures to adopt ML are clarified. Given the extensiveness of the research
area, challenges and unresolved issues are presented to facilitate future
studies, where ML based network slicing, infrastructure update to support ML
based paradigms, open data sets and platforms for researchers, theoretical
guidance for ML implementation and so on are discussed.Comment: 34 pages,8 figure
Distributed Virtual Resource Allocation in Small Cell Networks with Full Duplex Self-backhauls and Virtualization
Wireless network virtualization has attracted great attentions from both
academia and industry. Another emerging technology for next generation wireless
networks is in-band full duplex (FD) communications. Due to its promising
performance, FD communication has been considered as an effective way to
achieve self-backhauls for small cells. In this paper, we introduce wireless
virtualization into small cell networks, and propose a virtualized small cell
network architecture with FD self-backhauls. We formulate the virtual resource
allocation problem in virtualized small cell networks with FD self-backhauls as
an optimization problem. Since the formulated problem is a mixed combinatorial
and non-convex optimization problem, its computational complexity is high.
Moreover, the centralized scheme may suffer from signaling overhead, outdated
dynamics information, and scalability issues. To solve it efficiently, we
divide the original problem into two subproblems. For the first subproblem, we
transfer it to a convex optimization problem, and then solve it by an efficient
alternating direction method of multipliers (ADMM)-based distributed algorithm.
The second subproblem is a convex problem, which can be solved by each
infrastructure provider. Extensive simulations are conducted with different
system configurations to show the effectiveness of the proposed scheme
Small Cell Deployments: Recent Advances and Research Challenges
This paper summarizes the outcomes of the 5th International Workshop on
Femtocells held at King's College London, UK, on the 13th and 14th of February,
2012.The workshop hosted cutting-edge presentations about the latest advances
and research challenges in small cell roll-outs and heterogeneous cellular
networks. This paper provides some cutting edge information on the developments
of Self-Organizing Networks (SON) for small cell deployments, as well as
related standardization supports on issues such as carrier aggregation (CA),
Multiple-Input-Multiple-Output (MIMO) techniques, and enhanced Inter-Cell
Interference Coordination (eICIC), etc. Furthermore, some recent efforts on
issues such as energy-saving as well as Machine Learning (ML) techniques on
resource allocation and multi-cell cooperation are described. Finally, current
developments on simulation tools and small cell deployment scenarios are
presented. These topics collectively represent the current trends in small cell
deployments.Comment: 19 pages, 22 figure
Harvest the potential of massive MIMO with multi-layer techniques
Massive MIMO is envisioned as a promising technology for 5G wireless networks
due to its high potential to improve both spectral and energy efficiency.
Although the massive MIMO system is based on innovations in the physical layer,
the upper layer techniques also play important roles in harvesting the
performance gains of massive MIMO. In this article, we begin with an analysis
of the benefits and challenges of massive MIMO systems. We then investigate the
multi-layer techniques for incorporating massive MIMO in several important
network deployment scenarios. We conclude this article with a discussion of
open and potential problems for future research.Comment: IEEE Networ
Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues
As a promising paradigm to reduce both capital and operating expenditures,
the cloud radio access network (C-RAN) has been shown to provide high spectral
efficiency and energy efficiency. Motivated by its significant theoretical
performance gains and potential advantages, C-RANs have been advocated by both
the industry and research community. This paper comprehensively surveys the
recent advances of C-RANs, including system architectures, key techniques, and
open issues. The system architectures with different functional splits and the
corresponding characteristics are comprehensively summarized and discussed. The
state-of-the-art key techniques in C-RANs are classified as: the fronthaul
compression, large-scale collaborative processing, and channel estimation in
the physical layer; and the radio resource allocation and optimization in the
upper layer. Additionally, given the extensiveness of the research area, open
issues and challenges are presented to spur future investigations, in which the
involvement of edge cache, big data mining, social-aware device-to-device,
cognitive radio, software defined network, and physical layer security for
C-RANs are discussed, and the progress of testbed development and trial test
are introduced as well.Comment: 27 pages, 11 figure
Information-Centric Wireless Networks with Mobile Edge Computing
In order to better accommodate the dramatically increasing demand for data
caching and computing services, storage and computation capabilities should be
endowed to some of the intermediate nodes within the network. In this paper, we
design a novel virtualized heterogeneous networks framework aiming at enabling
content caching and computing. With the virtualization of the whole system, the
communication, computing and caching resources can be shared among all users
associated with different virtual service providers. We formulate the virtual
resource allocation strategy as a joint optimization problem, where the gains
of not only virtualization but also caching and computing are taken into
consideration in the proposed architecture. In addition, a distributed
algorithm based on alternating direction method of multipliers is adopted to
solve the formulated problem, in order to reduce the computational complexity
and signaling overhead. Finally, extensive simulations are presented to show
the effectiveness of the proposed scheme under different system parameters
Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks
With years of tremendous traffic and energy consumption growth, green radio
has been valued not only for theoretical research interests but also for the
operational expenditure reduction and the sustainable development of wireless
communications. Fundamental green tradeoffs, served as an important framework
for analysis, include four basic relationships: spectrum efficiency (SE) versus
energy efficiency (EE), deployment efficiency (DE) versus energy efficiency
(EE), delay (DL) versus power (PW), and bandwidth (BW) versus power (PW). In
this paper, we first provide a comprehensive overview on the extensive on-going
research efforts and categorize them based on the fundamental green tradeoffs.
We will then focus on research progresses of 4G and 5G communications, such as
orthogonal frequency division multiplexing (OFDM) and non-orthogonal
aggregation (NOA), multiple input multiple output (MIMO), and heterogeneous
networks (HetNets). We will also discuss potential challenges and impacts of
fundamental green tradeoffs, to shed some light on the energy efficient
research and design for future wireless networks.Comment: revised from IEEE Communications Surveys & Tutorial
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