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Applications of Cognitive Radio Networks: Recent Advances and Future Directions

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International Journal of Distributed Sensor Networks
Authors:
Sung Won Kim at Yeungnam University
Sung Won Kim
Miao Pan
Miao Pan
Miao Pan
  • This person is not on ResearchGate, or hasn't claimed this research yet.
Gyanendra Prasad Joshi at Sejong University
Gyanendra Prasad Joshi
Orhan Gazi
Orhan Gazi
Orhan Gazi
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Abstract

This work was supported by the 2015 Yeungnam University Research Grant. Finally, we thank all the authors who submitted their work to this special issue and many experts who participated in the review process. We expect that this issue will certainly help researchers, academicians, practitioners, and industrialists to realize the recent advances and also may help them to work in the future directions.
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Editorial
Applications of Cognitive Radio Networks:
Recent Advances and Future Directions
Sung W. Kim,1Miao Pan,2Gyanendra Prasad Joshi,1Orhan Gazi,3
Jianhua He,4and Marceau Coupechoux5
1Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
2Department of Computer Science, Texas Southern University, Houston, TX 77004, USA
3Department of Electric and Communication Engineering, Cankaya University, 06790 Ankara, Turkey
4Department of Electrical, Electronic and Power Engineering, Aston University, Birmingham B4 7ET, UK
5Department of Computer and Network Science, Telecom ParisTech, 75013 Paris, France
Correspondence should be addressed to Gyanendra Prasad Joshi; joshi@ynu.ac.kr
Received 13 December 2015; Accepted 14 December 2015
Copyright © 2016 Sung W. Kim et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Contemporary wireless networks must meet the ever increas-
ing bandwidth requirements to assure the quality of service
(QoS)totheendusers.Cognitiveradio(CR)technology
with ecient electromagnetic spectrum management can
achieve increased bandwidth beyond its traditional limits.
e innovative spectrum management by CRNs allows for
usage of incumbent spectrum band by unlicensed (cogni-
tive) users possibly without interfering with the incumbent
users. CR network is an intelligent and adaptive wireless
communications system in which CR devices learn from its
surroundings and decide the operation based on the learning.
CR devices are inevitably so intelligent that they can dynami-
cally choose carrier frequency, bandwidth, transmission rate,
transmission power, and so forth.
ere are many emerging CR networks applications based
on CR technologies. is special issue is focused on present-
ing state-of-the-art research results on the application of CR
networks. is is targeted for the innovative and productive
discussion on the recent advancement in the application of
CR networks and future directions.
e article “Convergence Research Directions in Cog-
nitive Sensor Networks for Elderly Housing Design” by S.
Suhetal.isabouttheapplicationofCRsensornetwork.It
denes smart home and surveys CR sensor network- (CRSN-
) based systems for elderly housing. is article proposes
research directions for the elderly smart home services based
onCRSN.Particularly,thearticleisfocusedonadopting
CRSN technologies to cope with dense sensors environment
and heterogeneous network environment. It also discusses
customizing sensors/networks classication correlated with
the elderly types, and converging sensor network technolo-
gies with architectural technologies.
A lightweight and robust mechanism that appropriately
securesthechannelselectionprocessispresentedinthe
article “A Cognitive-Radio-Based Method for Improving
Availability in Body Sensor Networks” by O. Le´
on et al. In
this article, authors describe a new network paradigm known
as cognitive body sensor networks (CBSNs). In the body
area networks, seamless connectivity is crucial and must be
guaranteed. Connectivity losses during emergency situations
may prevent a patient from immediately receiving medical
assistance and may end up in catastrophic results. is article
discusses how to prevent CBSNs from the specic attacks
by securing the sensing process. e proposed method
relies on cryptographic primitives that require a minimum
amount of memory and low energy consumption, thus being
more suited for devices with limited resources. It oers
authentication and encryption of control data shared by the
sensorsintheCBSNtoagreeonagivenchannel.
An energy-ecient layered video multicast (LVM) trans-
mission over OFDM-based CR systems for “bandwidth-
hungry” video services is presented in the article entitled
Hindawi Publishing Corporation
International Journal of Distributed Sensor Networks
Volume 2016, Article ID 4964068, 2 pages
http://dx.doi.org/10.1155/2016/4964068
2 International Journal of Distributed Sensor Networks
“Energy-Ecient Layered Video Multicast over OFDM-
BasedCognitiveRadioSystems”byW.Xuetal.isarticle
proposes an energy utility- (EU-) based power allocation
algorithm by jointly employing fractional programming and
subgradient method. e novel performance metric EU is
proposed to measure the sum of achieved quality of recon-
structed video at all subscribers when unit transmit power
is consumed. e objective is to maximize the system EU
by jointly optimizing the intersession/interlayer subcarrier
assignment and subsequent power allocation. To achieve the
objective, it performs subcarrier assignment for base layer
and enhancement layers using greedy algorithm and then
presents an optimal power allocation algorithm to maximize
the achievable EU using fractional programming.
In the article “A Cross-Layer-Based Routing Protocol for
Ad Hoc Cognitive Radio Networks” by G. P. Joshi et al.,
the authors propose a cross-layer-based routing protocol for
mobile ad hoc CR networks. e motivation for this paper
is that rerouting is expensive in terms of energy, delay, and
throughput. us, it is better to select a route in such a way
that requires less channel switching. is paper examines the
expectation of channel switching in the range of scenarios
and proposes a novel route selection method to mitigate the
frequent channel switching. Because excessive workload on
a particular node causes network partitioning and induces
repeated rerouting, the proposed protocol distributes the
routing overheads among cognitive users in the network and
prolongs the network lifetime. is protocol incorporates
power awareness and spectrum information with a cross-
layer approach.
e Sensor Virtualization Module (SVM) is proposed in
the article “Sensor Virtualization Module: Virtualizing IoT
Devices on Mobile Smartphones for Eective Sensor Data
Management” by J. Ko et al. ere are limited IoT resource-
utilizing applications due to the traditional stovepipe soware
architecture, where the vendors provide supporting soware
on an end-to-end basis. e proposed SVM in this article
provides a soware abstraction for external IoT objects and
allows applications to easily utilize various IoT resources
through open APIs. It also presents the applications with a
common virtualized environment where external IoT devices
can be easily accessed from and via mobile computing
platforms.
In the article “An Analytical Approach to Opportunistic
Transmission under Rayleigh Fading Channels” by Y. B.
Zikria et al., the authors present the eectiveness of the
opportunistic transmission in terms of reliability and delay
of transmission analytically. A xed-distance-based statistical
model is proposed for multihop and opportunistic trans-
mission for CRSNs. Also, a unique generic Markov chain
modelisproposedtoshowthestabilityofopportunistic
transmission.
Acknowledgments
is work was supported by the 2015 Yeungnam University
Research Grant. Finally, we thank all the authors who sub-
mitted their work to this special issue and many experts who
participated in the review process. We expect that this issue
will certainly help researchers, academicians, practitioners,
and industrialists to realize the recent advances and also may
help them to work in the future directions.
Sung W. Kim
Miao Pan
Gyanendra Prasad Joshi
Orhan Gazi
Jianhua He
Marceau Coupechoux
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Distributed
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International Journal of
... Such information may not be inferred or known by the SU. To take account of the maximum quantity of generality and while keeping the analytical traceability, we thus develop the OFF-ON activity model of the PUs as both the alternative renewal process [31,32]: P n OFF , P n ON , n ≥ 1, where n indicates the number of renewal OFF-ON evacuated up to the instant t. The duration of the entire OFF (P n OFF ) period or the ON P n ON period, is designated as a random variable that is distributed according to a probability density function and is autonomous compared to other OFF or ON periods [33]. ...
... In reality, an SU has the ability to access several channels. Different protocols and architectures have been suggested in order to discover and facilitate access to these channels [31]. In order not to introduce architectural details that can all time restrict the generality of the results and make our Information 2018, 9, 323 5 of 20 analysis complicated, we decide to keep the only stochastic process ON-OFF. ...
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View
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The concept of cognitive radio (CR) is a new paradigm that autonomously discover the demographics of radio spectrum to get information about its utilization and determine the services being offered. The prospect usage of CR architectures in future generations of wireless communications is very promising. CR basically integrates machine learning algorithms into wireless devices and networks. It is evolving from self awareness stage to cognitive learning autonomously about its environment which would be helpful to adapt to new wireless standards, access users environment and behavior. A fundamental part in a CR is its front-end antenna system. The function of such antennas are self-awareness by scanning the entire spectrum of interest along with provides serving by reconfigurable antennas over several bands. In the near future, CR platforms will be integrated to become a part of wireless communication standards. The front end of a CR consists of a sensing antenna for spectrum scanning and a reconfigurable antenna or reconfigurable multiple-input-multiple-output (MIMO) antenna system for communication over several frequency bands. Reconfigurable antennas in CR applications are used to vary its fundamental properties to efficiently utilize the available bandwidth while MIMO antenna system based reconfigurable antennas are to be used to meet the high data rate requirements of future wireless terminals. This chapter will shine some light on the most recent CR front-end antennas focusing on MIMO based integrated architecture.
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... This displays the join's capacity to mind and gets at data using a crosslayer method. [52][53][54] Challenges, limitations, and strength ...
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Cognitive radios are expected to play an important role in capturing the constantly growing traffic interest on remote networks. To improve the usage of the radio range, a cognitive radio hub detects the weather, evaluates the open-air qualities, and then makes certain decisions and distributes the executives’ space assets. The cognitive radio works in tandem with artificial intelligence and artificial intelligence methodologies to provide a flexible and intelligent allocation for continuous production cycles. The purpose is to provide a single source of information in the form of a survey research to enable academics better understand how artificial intelligence methodologies, such as fuzzy logics, genetic algorithms, and artificial neural networks, are used to various cognitive radio systems. The various artificial intelligence approaches used in cognitive radio engines to improve cognition capabilities in cognitive radio networks are examined in this study. Computerized reasoning approaches, such as fuzzy logic, evolutionary algorithms, and artificial neural networks, are used in the writing audit. This topic also covers cognitive radio network implementation and the typical learning challenges that arise in cognitive radio systems.
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End-to-end application performance and throughput of vehicular cognitive transport control protocol depend on how efficiently the segments (TCP header) are being transmitted from source to destination. One way to enhance the performance of vehicular cognitive TCP protocol is by reducing the packet drops in between the source and destination. In general, packet drops occur in between the source and destination of Cognitive Radio Vehicular Ad Hoc Network (CR-VANET) because of spectrum handoff or cognitive node handoff, or network congestion. In this paper, we focus on enhancing the performance of cognitive TCP protocol through “cognitive AODV routing protocol with the spectrum handoff mechanism.” In the proposed work, channel-route control messages of cognitive AODV routing protocol are updated with the support of spectrum handoff which helps to provide the backup opportunistic channel during PU active and helps to reduce the end-to-end spectrum handoff packet drops. Simulation results reveal that the overall performance of the vehicular cognitive TCP protocol with the proposed spectrum handoff aware cognitive AODV routing protocol is enhanced as compared to the existing cognitive TCP protocol.
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