13,342 research outputs found
On Green Energy Powered Cognitive Radio Networks
Green energy powered cognitive radio (CR) network is capable of liberating
the wireless access networks from spectral and energy constraints. The
limitation of the spectrum is alleviated by exploiting cognitive networking in
which wireless nodes sense and utilize the spare spectrum for data
communications, while dependence on the traditional unsustainable energy is
assuaged by adopting energy harvesting (EH) through which green energy can be
harnessed to power wireless networks. Green energy powered CR increases the
network availability and thus extends emerging network applications. Designing
green CR networks is challenging. It requires not only the optimization of
dynamic spectrum access but also the optimal utilization of green energy. This
paper surveys the energy efficient cognitive radio techniques and the
optimization of green energy powered wireless networks. Existing works on
energy aware spectrum sensing, management, and sharing are investigated in
detail. The state of the art of the energy efficient CR based wireless access
network is discussed in various aspects such as relay and cooperative radio and
small cells. Envisioning green energy as an important energy resource in the
future, network performance highly depends on the dynamics of the available
spectrum and green energy. As compared with the traditional energy source, the
arrival rate of green energy, which highly depends on the environment of the
energy harvesters, is rather random and intermittent. To optimize and adapt the
usage of green energy according to the opportunistic spectrum availability, we
discuss research challenges in designing cognitive radio networks which are
powered by energy harvesters
Effective Capacity in Wireless Networks: A Comprehensive Survey
Low latency applications, such as multimedia communications, autonomous
vehicles, and Tactile Internet are the emerging applications for
next-generation wireless networks, such as 5th generation (5G) mobile networks.
Existing physical-layer channel models, however, do not explicitly consider
quality-of-service (QoS) aware related parameters under specific delay
constraints. To investigate the performance of low-latency applications in
future networks, a new mathematical framework is needed. Effective capacity
(EC), which is a link-layer channel model with QoS-awareness, can be used to
investigate the performance of wireless networks under certain statistical
delay constraints. In this paper, we provide a comprehensive survey on existing
works, that use the EC model in various wireless networks. We summarize the
work related to EC for different networks such as cognitive radio networks
(CRNs), cellular networks, relay networks, adhoc networks, and mesh networks.
We explore five case studies encompassing EC operation with different design
and architectural requirements. We survey various delay-sensitive applications
such as voice and video with their EC analysis under certain delay constraints.
We finally present the future research directions with open issues covering EC
maximization
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
A Survey on Device-to-Device Communication in Cellular Networks
Device-to-Device (D2D) communication was initially proposed in cellular
networks as a new paradigm to enhance network performance. The emergence of new
applications such as content distribution and location-aware advertisement
introduced new use-cases for D2D communications in cellular networks. The
initial studies showed that D2D communication has advantages such as increased
spectral efficiency and reduced communication delay. However, this
communication mode introduces complications in terms of interference control
overhead and protocols that are still open research problems. The feasibility
of D2D communications in LTE-A is being studied by academia, industry, and the
standardization bodies. To date, there are more than 100 papers available on
D2D communications in cellular networks and, there is no survey on this field.
In this article, we provide a taxonomy based on the D2D communicating spectrum
and review the available literature extensively under the proposed taxonomy.
Moreover, we provide new insights to the over-explored and under-explored areas
which lead us to identify open research problems of D2D communication in
cellular networks.Comment: 18 pages; 8 figures; Accepted for publication in IEEE Communications
Surveys and Tutorial
Greedy-Knapsack Algorithm for Optimal Downlink Resource Allocation in LTE Networks
The Long Term Evolution (LTE) as a mobile broadband technology supports a
wide domain of communication services with different requirements. Therefore,
scheduling of all flows from various applications in overload states in which
the requested amount of bandwidth exceeds the limited available spectrum
resources is a challenging issue. Accordingly, in this paper, a greedy
algorithm is presented to evaluate user candidates which are waiting for
scheduling and select an optimal set of the users to maximize system
performance, without exceeding available bandwidth capacity. The
greedy-knapsack algorithm is defined as an optimal solution to the resource
allocation problem, formulated based on the fractional knapsack problem. A
compromise between throughput and QoS provisioning is obtained by proposing a
class-based ranking function, which is a combination of throughput and QoS
related parameters defined for each application. The simulation results show
that the proposed method provides high performance in terms of throughput, loss
and delay for different classes of QoS over the existing ones, especially under
overload traffic.Comment: Wireless Networks, 201
Delay-Constrained Video Transmission: Quality-driven Resource Allocation and Scheduling
Real-time video demands quality-of-service (QoS) guarantees such as delay
bounds for end-user satisfaction. Furthermore, the tolerable delay varies
depending on the use case such as live streaming or two-way video conferencing.
Due to the inherently stochastic nature of wireless fading channels,
deterministic delay bounds are difficult to guarantee. Instead, we propose
providing statistical delay guarantees using the concept of effective capacity.
We consider a multiuser setup whereby different users have (possibly different)
delay QoS constraints. We derive the resource allocation policy that maximizes
the sum video quality and applies to any quality metric with concave
rate-quality mapping. We show that the optimal operating point per user is such
that the rate-distortion slope is the inverse of the supported video source
rate per unit bandwidth, a key metric we refer to as the source spectral
efficiency. We also solve the alternative problem of fairness-based resource
allocation whereby the objective is to maximize the minimum video quality
across users. Finally, we derive user admission and scheduling policies that
enable selecting a maximal user subset such that all selected users can meet
their statistical delay requirement. Results show that video users with
differentiated QoS requirements can achieve similar video quality with vastly
different resource requirements. Thus, QoS-aware scheduling and resource
allocation enable supporting significantly more users under the same resource
constraints.Comment: Submitted to IEEE Journal of Selected Topics in Signal Processin
A Survey on Cross-Layer Design Frameworks for Multimedia Applications over Wireless Networks
In the last few years, the Internet throughput, usage and reliability have
increased almost exponentially. The introduction of broadband wireless mobile
ad hoc networks (MANETs) and cellular networks together with increased
computational power have opened the door for a new breed of applications to be
created, namely real-time multimedia applications. Delivering real-time
multimedia traffic over a complex network like the Internet is a particularly
challenging task since these applications have strict quality -of-service (QoS)
requirements on bandwidth, delay, and delay jitter. Traditional IP-based best
effort service will not be able to meet these stringent requirements. The
time-varying nature of wireless channels and resource constrained wireless
devices make the problem even more difficult. To improve perceived media
quality by end users over wireless Internet, QoS supports can be addressed in
different layers, including application layer, transport layer and link layer.
Cross layer design is a well-known approach to achieve this adaptation. In
cross-layer design, the challenges from the physical wireless medium and the
QoS-demands from the applications are taken into account so that the rate,
power, and coding at the physical layer can adapted to meet the requirements of
the applications given the current channel and network conditions. A number of
propositions for cross-layer designs exist in the literature. In this paper, an
extensive review has been made on these cross-layer architectures that combine
the application-layer, transport layer and the link layer controls.
Particularly the issues like channel estimation techniques, adaptive controls
at the application and link layers for energy efficiency, priority based
scheduling, transmission rate control at the transport layer, and adaptive
automatic repeat request (ARQ) are discussed in detail.Comment: 16 pages, 9 figure
Cross-Layer Scheduling for OFDMA-based Cognitive Radio Systems with Delay and Security Constraints
This paper considers the resource allocation problem in an Orthogonal
Frequency Division Multiple Access (OFDMA) based cognitive radio (CR) network,
where the CR base station adopts full overlay scheme to transmit both private
and open information to multiple users with average delay and power
constraints. A stochastic optimization problem is formulated to develop flow
control and radio resource allocation in order to maximize the long-term system
throughput of open and private information in CR system and ensure the
stability of primary system. The corresponding optimal condition for employing
full overlay is derived in the context of concurrent transmission of open and
private information. An online resource allocation scheme is designed to adapt
the transmission of open and private information based on monitoring the status
of primary system as well as the channel and queue states in the CR network.
The scheme is proven to be asymptotically optimal in solving the stochastic
optimization problem without knowing any statistical information. Simulations
are provided to verify the analytical results and efficiency of the scheme
Intercell Interference-Aware Scheduling for Delay Sensitive Applications in C-RAN
Cloud radio access network (C-RAN) architecture is a new mobile network
architecture that enables cooperative baseband processing and information
sharing among multiple cells and achieves high adaptability to nonuniform
traffic by centralizing the baseband processing resources in a virtualized
baseband unit (BBU) pool. In this work, we formulate the utility of each user
using a convex delay cost function, and design a two-step scheduling algorithm
with good delay performance for the C-RAN architecture. In the first step, all
users in multiple cells are grouped into small user groups, according to their
interference levels and estimated utilities. In the second step, channels are
matched to the user groups to maximize the system utility. The performance of
our algorithm is further studied via simulations, and the advantages of C-RAN
architecture is verified
A Survey on QoE-oriented Wireless Resources Scheduling
Future wireless systems are expected to provide a wide range of services to
more and more users. Advanced scheduling strategies thus arise not only to
perform efficient radio resource management, but also to provide fairness among
the users. On the other hand, the users' perceived quality, i.e., Quality of
Experience (QoE), is becoming one of the main drivers within the schedulers
design. In this context, this paper starts by providing a comprehension of what
is QoE and an overview of the evolution of wireless scheduling techniques.
Afterwards, a survey on the most recent QoE-based scheduling strategies for
wireless systems is presented, highlighting the application/service of the
different approaches reported in the literature, as well as the parameters that
were taken into account for QoE optimization. Therefore, this paper aims at
helping readers interested in learning the basic concepts of QoE-oriented
wireless resources scheduling, as well as getting in touch with its current
research frontier.Comment: Revised version: updated according to the most recent related
literature; added references; corrected typo
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