10,076 research outputs found
Transport Protocols in Cognitive Radio Networks: A Survey
Cognitive radio networks (CRNs) have emerged as a promising solution to
enhance spectrum utilization by using unused or less used spectrum in radio
environments. The basic idea of CRNs is to allow secondary users (SUs) access
to licensed spectrum, under the condition that the interference perceived by
the primary users (PUs) is minimal. In CRNs, the channel availability is
uncertainty due to the existence of PUs, resulting in intermittent
communication. Transmission control protocol (TCP) performance may
significantly degrade in such conditions. To address the challenges, some
transport protocols have been proposed for reliable transmission in CRNs. In
this paper we survey the state-of-the-art transport protocols for CRNs. We
firstly highlight the unique aspects of CRNs, and describe the challenges of
transport protocols in terms of PU behavior, spectrum sensing, spectrum
changing and TCP mechanism itself over CRNs. Then, we provide a summary and
comparison of existing transport protocols for CRNs. Finally, we discuss
several open issues and research challenges. To the best of our knowledge, our
work is the first survey on transport protocols for CRNs.Comment: to appear in KSII Transactions on Internet and Information System
Performance Evaluation of QoS Parameters in Dynamic Spectrum Sharing for Heterogeneous Wireless Communication Networks
Cognitive radio nodes have been proposed as means to improve the spectrum
utilization. It reuses the spectrum of a primary service provider under the
condition that the primary service provider services are not harmfully
interrupted. A cognitive radio can sense its operating environment's conditions
and it is able to reconfigure itself and to communicate with other counterparts
based on the status of the environment and also the requirements of the user to
meet the optimal communication conditions and to keep quality of service (QoS)
as high as possible. The efficiency of spectrum sharing can be improved by
minimizing the interference. The Utility function that captures the cooperative
behavior to minimize the interference and the satisfaction to improve the
throughput is investigated. The dynamic spectrum sharing algorithm can maintain
the quality of service (QoS) of each network while the effective spectrum
utilisation is improved under a fluctuation traffic environment when the
available spectrum is limited.Comment: IJCSI International Journal of Computer Science Issues, Vol. 9, Issue
1, No 2, January 2012 ISSN (Online): 1694-0814 http://www.IJCSI.or
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
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
Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning
The ability to intelligently utilize resources to meet the need of growing
diversity in services and user behavior marks the future of wireless
communication systems. Intelligent wireless communications aims at enabling the
system to perceive and assess the available resources, to autonomously learn to
adapt to the perceived wireless environment, and to reconfigure its operating
mode to maximize the utility of the available resources. The perception
capability and reconfigurability are the essential features of cognitive radio
while modern machine learning techniques project great potential in system
adaptation. In this paper, we discuss the development of the cognitive radio
technology and machine learning techniques and emphasize their roles in
improving spectrum and energy utility of wireless communication systems. We
describe the state-of-the-art of relevant techniques, covering spectrum sensing
and access approaches and powerful machine learning algorithms that enable
spectrum- and energy-efficient communications in dynamic wireless environments.
We also present practical applications of these techniques and identify further
research challenges in cognitive radio and machine learning as applied to the
existing and future wireless communication systems
Throughput Enhancement of Multicarrier Cognitive M2M Networks: Universal-Filtered OFDM Systems
We consider a cognitive radio network consisting of a primary cellular system
and a secondary cognitive machine-to-machine (M2M) system, and study the
throughput enhancement problem of the latter system employing
universal-filtered orthogonal frequency division multiplexing (UF-OFDM)
modulation. The downlink transmission capacity of the cognitive M2M system is
thereby maximized, while keeping the interference introduced to the primary
users (PUs) below the pre-specified threshold, under total transmit power
budget of the secondary base station (SBS). The performance of UF-OFDM based CR
system is compared to the performances of OFDM-based and filter bank
multicarrier (FBMC)-based CR systems. We also propose a near-optimal resource
allocation method separating the subband and power allocation. The solution is
less complex compared to optimization of the original combinatorial problem. We
present numerical results that show that for given interference thresholds of
the PUs and maximum transmit power limit of the SBS, the UF-OFDM based CR
system exhibits intermediary performance in terms of achievable capacity
compared to OFDM and FBMC-based CR systems. Interestingly, for a certain degree
of robustness of the PUs, the UF-OFDM performs equally well as FBMC.
Furthermore, the percentage rate-gain of UF-OFDM based CR system increases by a
large amount when UF-OFDM modulation with lower sidelobes ripple is employed.
Numerical results also show that the proposed throughput enhancing method
despite having lower computational complexity compared to the optimal solution
achieves near-optimal performance
Performance Analysis of Wireless Network with Opportunistic Spectrum Sharing via Cognitive Radio Nodes
Cognitive radio (CR) is found to be an emerging key for efficient spectrum
utilization. In this paper, spectrum sharing among service providers with the
help of cognitive radio has been investigated. The technique of spectrum
sharing among service providers to share the licensed spectrum of licensed
service providers in a dynamic manner is considered. The performance of the
wireless network with opportunistic spectrum sharing techniques is analyzed.
Thus, the spectral utilization and efficiency of sensing is increased, the
interference is minimized, and the call blockage is reduced.Comment: 10 Pages, Journal of Electronic Science and Technology, Vol. 10, No.
4, December 2012. arXiv admin note: text overlap with arXiv:1210.3435; and
with arXiv:1201.1964 by other authors without attributio
All Technologies Work Together for Good: A Glance to Future Mobile Networks
The astounding capacity requirements of 5G have motivated researchers to
investigate the feasibility of many potential technologies, such as massive
multiple-input multiple-output, millimeter wave, full-duplex, non-orthogonal
multiple access, carrier aggregation, cognitive radio, and network
ultra-densification. The benefits and challenges of these technologies have
been thoroughly studied either individually or in a combination of two or
three. It is not clear, however, whether all potential technologies operating
together lead to fulfilling the requirements posed by 5G. This paper explores
the potential benefits and challenges when all technologies coexist in an
ultra-dense cellular environment. The sum rate of the network is investigated
with respect to the increase in the number of small-cells and results show the
capacity gains achieved by the coexistence.Comment: Accepted for publication in IEEE Wireless Communication, Special
Issue-5G mmWave Small Cell Networks: Architecture, Self-Organization and
Managemen
Green Sensing and Access: Energy-Throughput Tradeoffs in Cognitive Networking
Limited spectrum resources and dramatic growth of high data rate applications
have motivated opportunistic spectrum access utilizing the promising concept of
cognitive networks. Although this concept has emerged primarily to enhance
spectrum utilization and to allow the coexistence of heterogeneous network
technologies, the importance of energy consumption imposes additional
challenges, because energy consumption and communication performance can be at
odds. In this paper, the approaches for energy efficient spectrum sensing and
spectrum handoff, fundamental building blocks of cognitive networks is
investigated. The tradeoff between energy consumption and throughput, under
local as well as under cooperative sensing are characterized, and what further
aspects need to be investigated to achieve energy efficient cognitive operation
under various application requirements are discussed.Comment: to be published in IEEE Communications Magazine, 8 pages, 1 table, 6
figures. arXiv admin note: substantial text overlap with arXiv:1312.004
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
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